It is of great significance to accurately and rapidly identify shale lithofacies in relation to the evaluation and prediction of sweet spots for shale oil and gas reservoirs.To address the problem of low resolution in...It is of great significance to accurately and rapidly identify shale lithofacies in relation to the evaluation and prediction of sweet spots for shale oil and gas reservoirs.To address the problem of low resolution in logging curves,this study establishes a grayscale-phase model based on high-resolution grayscale curves using clustering analysis algorithms for shale lithofacies identification,working with the Shahejie For-mation,Bohai Bay Basin,China.The grayscale phase is defined as the sum of absolute grayscale and relative amplitude as well as their features.The absolute grayscale is the absolute magnitude of the gray values and is utilized for evaluating the material composition(mineral composition+total organic carbon)of shale,while the relative amplitude is the difference between adjacent gray values and is used to identify the shale structure type.The research results show that the grayscale phase model can identify shale lithofacies well,and the accuracy and applicability of this model were verified by the fitting relationship between absolute grayscale and shale mineral composition,as well as corresponding re-lationships between relative amplitudes and laminae development in shales.Four lithofacies are iden-tified in the target layer of the study area:massive mixed shale,laminated mixed shale,massive calcareous shale and laminated calcareous shale.This method can not only effectively characterize the material composition of shale,but also numerically characterize the development degree of shale laminae,and solve the problem that difficult to identify millimeter-scale laminae based on logging curves,which can provide technical support for shale lithofacies identification,sweet spot evaluation and prediction of complex continental lacustrine basins.展开更多
Dynamic infrared scene simulation is for discovering and solving the problems encountered in designing, developing and manufacturing infrared imaging guidance weapons. The infrared scene simulation is explored by usin...Dynamic infrared scene simulation is for discovering and solving the problems encountered in designing, developing and manufacturing infrared imaging guidance weapons. The infrared scene simulation is explored by using the digital grayscale modulation method. The infrared image modulation model of a digital micro-mirror device （DMD） is established and then the infrared scene simulator prototype which is based on DMD grayscale modulation is developed. To evaluate its main parameters such as resolution, contrast, minimum temperature difference, gray scale, various DMD subsystems such as signal decoding, image normalization, synchronization drive, pulse width modulation （PWM） and DMD chips are designed. The infrared scene simulator is tested on a certain infrared missile seeker. The test results show preliminarily that the infrared scene simulator has high gray scale, small geometrical distortion and highly resolvable imaging resolution and contrast and yields high-fidelity images, thus being able to meet the requirements for the infrared scene simulation inside a laboratory.展开更多
Doped elements in alloys significantly impact their performance.Conventional methods usually sputter the surface material of the sample,or their performance is limited to the surface of alloys owing to their poor pene...Doped elements in alloys significantly impact their performance.Conventional methods usually sputter the surface material of the sample,or their performance is limited to the surface of alloys owing to their poor penetration ability.The X-ray K-edge subtraction(KES)method exhibits great potential for the nondestructive in situ detection of element contents in alloys.However,the signal of doped elements usually deteriorates because of the strong absorption of the principal component and scattering of crystal grains.This in turn prevents the extensive application of X-ray KES imaging to alloys.In this study,methods were developed to calibrate the linearity between the grayscale of the KES image and element content.The methods were aimed at the sensitive analysis of elements in alloys.Furthermore,experiments with phantoms and alloys demonstrated that,after elaborate calibration,X-ray KES imaging is capable of nondestructive and sensitive analysis of doped elements in alloys.展开更多
Structural color from artificial structures,due to its environmental friendliness and excellent durability,represents a route for color printing applications.Among various physical mechanisms,the Fabry–Perot(F–P)cav...Structural color from artificial structures,due to its environmental friendliness and excellent durability,represents a route for color printing applications.Among various physical mechanisms,the Fabry–Perot(F–P)cavity effect provides a powerful way to generate vivid colors in either the reflection or transmission direction.Most of the previous F–P type color printing works rely on electron beam grayscale lithography,however,with this technique it is challenging to make large-area and low-cost devices.To circumvent this constraint,we propose to fabricate the F–P type color printing device by the laser grayscale lithography process.The F–P cavity consists of two thin silver films as mirrors and a photoresist film with a spatially variant thickness as the spacer layer.By controlling the laser exposure dose pixel by pixel,a centimeter-scale fullcolor printing device with a spatial resolution up to 5μm×5μm is demonstrated.The proposed large area color printing device may have great potential in practical application areas such as color displays,hyperspectral imaging,advanced painting,and so on.展开更多
There are many detectors for the least significant bit(LSB)steganography which is broadly used in hiding information in the digital images.The length of the hidden information is one of the most important parameters i...There are many detectors for the least significant bit(LSB)steganography which is broadly used in hiding information in the digital images.The length of the hidden information is one of the most important parameters in detecting steganographic information.Using 2-D gradient of a pixel and the distance between variables the proposed method gives the length of hidden information in natural grayscale images without original image.Extensive experimental results show good performance even at low embedding rate compared with other methods.Furthermore,the proposed method also works well disregarding the status of the embedded information.展开更多
This document describes the use of grayscale mapping and GIS for identification of historical irrigated lands. Historical irrigated lands form the basis for water rights—a private property right in New Mexico that is...This document describes the use of grayscale mapping and GIS for identification of historical irrigated lands. Historical irrigated lands form the basis for water rights—a private property right in New Mexico that is bought and sold on the open market. Identification of irrigated land on historical photography is both a science and an art. Grayscale mapping of historic black and white photographs can aid in the identification of irrigated lands. GIS allows historical images to be geo-referenced and area computations to be performed on polygons that define the irrigated lands.展开更多
Near-InfraRed(NIR)imaging technology plays a pivotal role in assisted driving and safety surveillance systems,yet its monochromatic nature and deficiency in detail limit its further application.Recent methods aim to r...Near-InfraRed(NIR)imaging technology plays a pivotal role in assisted driving and safety surveillance systems,yet its monochromatic nature and deficiency in detail limit its further application.Recent methods aim to recover the corresponding RGB image directly from the NIR image using Convolutional Neural Networks(CNN).However,these methods struggle with accurately recovering both luminance and chrominance information and the inherent deficiencies in NIR image details.In this paper,we propose grayscale-assisted RGB image restoration from NIR images to recover luminance and chrominance information in two stages.We address the complex NIR-to-RGB conversion challenge by decoupling it into two separate stages.First,it converts NIR to grayscale images,focusing on luminance learning.Then,it transforms grayscale to RGB images,concentrating on chrominance information.In addition,we incorporate frequency domain learning to shift the image processing from the spatial domain to the frequency domain,facilitating the restoration of the detailed textures often lost in NIR images.Empirical evaluations of our grayscale-assisted framework and existing state-of-the-art methods demonstrate its superior performance and yield more visually appealing results.Code is accessible at:https://github.com/Yiiclass/RING.展开更多
Images perceived by human eyes or recorded by cameras are usually optical patterns with spatially varying intensity or color profiles.In addition to the intensity and color,the information of an image can be encoded i...Images perceived by human eyes or recorded by cameras are usually optical patterns with spatially varying intensity or color profiles.In addition to the intensity and color,the information of an image can be encoded in a spatially varying distribution of phase or polarization state.Interestingly,such images might not be able to be directly viewed by human eyes or cameras because they may exhibit highly uniform intensity profiles.Here,we propose and experimentally demonstrate an approach to hide a high-resolution grayscale image in a square laser beam with a size of less than half a millimeter.An image with a pixel size of 300×300 nm is encoded into the spatially variant polarization states of the laser beam,which can be revealed after passing through a linear polarizer.This unique technology for hiding grayscale images and polarization manipulation provides new opportunities for various applications,including encryption,imaging,optical communications,quantum science and fundamental physics.展开更多
In single-pixel imaging or computational ghost imaging,the measurement matrix has a great impact on the performance of the imaging system,because it involves modulation of the optical signal and image reconstruction.T...In single-pixel imaging or computational ghost imaging,the measurement matrix has a great impact on the performance of the imaging system,because it involves modulation of the optical signal and image reconstruction.The measurement matrix reported in the existing literatures is first binarized and then loaded onto the digital micro-mirror device(DMD)for optical modulation,that is,each pixel can only be modulated into on-off states.In this paper,we propose a digital grayscale modulation method for more efficient compressive sampling.On the basis of this,we demonstrate a single photon compressive imaging system.A control and counting circuit,based on field-programmable gate array(FPGA),is developed to control DMD to conduct digital grayscale modulation and count single-photon pulse output from the photomultiplier tube(PMT)simultaneously.The experimental results show that the imaging reconstruction quality can be improved by increasing the sparsity ratio properly and compressive sampling ratio(SR)of these gray-scale matrices.However,when the compressive SR and sparsity ratio are increased appropriately to a certain value,the reconstruction quality is usually saturated,and the imaging reconstruction quality of the digital grayscale modulation is better than that of binary modulation.展开更多
Background:Grayscale image attributes of computed tomography(CT)of pulmonary scans contain valuable information relating to patients with respiratory ailments.These attributes are used to evaluate the severity of lung...Background:Grayscale image attributes of computed tomography(CT)of pulmonary scans contain valuable information relating to patients with respiratory ailments.These attributes are used to evaluate the severity of lung conditions of patients confirmed to be with and without COVID-19.Method:Five hundred thirteen CT images relating to 57 patients(49 with COVID-19;8 free of COVID-19)were collected at Namazi Medical Centre(Shiraz,Iran)in 2020 and 2021.Five visual scores(VS:0,1,2,3,or 4)are clinically assigned to these images with the score increasing with the severity of COVID-19-related lung conditions.Eleven deep learning and machine learning techniques(DL/ML)are used to distinguish the VS class based on 12 grayscale image attributes.Results:The convolutional neural network achieves 96.49%VS accuracy(18 errors from 513 images)successfully distinguishing VS Classes 0 and 1,outperforming clinicians’visual inspections.An algorithmic score(AS),involving just five grayscale image attributes,is developed independently of clinicians’assessments(99.81%AS accuracy;1 error from 513 images).Conclusion:Grayscale CT image attributes can be successfully used to distinguish the severity of COVID-19 lung damage.The AS technique developed provides a suitable basis for an automated system using ML/DL methods and 12 image attributes.展开更多
Achieving a high sensitivity for practical applications has always been one of the main developmental directions for wearable flexible pressure sensors.This paper introduces a laser speckle grayscale lithography syste...Achieving a high sensitivity for practical applications has always been one of the main developmental directions for wearable flexible pressure sensors.This paper introduces a laser speckle grayscale lithography system and a novel method for fabricating random conical array microstructures using grainy laser speckle patterns.Its feasibility is attributed to the autocorrelation function of the laser speckle intensity,which adheres to a first-order Bessel function of the first kind.Through objective speckle size and exposure dose manipulations,we developed a microstructured photoresist with various micromorphologies.These microstructures were used to form polydimethylsiloxane microstructured electrodes that were used in flexible capacitive pressure sensors.These-1 sensors exhibited an ultra-high sensitivity:19.76 kPa for the low-pressure range of 0-100 Pa.Their minimum detection threshold was 1.9 Pa,and they maintained stability and resilience over 10,000 test cycles.These sensors proved to be adept at capturing physiological signals and providing tactile feedback,thereby emphasizing their practical value.展开更多
Image coloring is an inherently uncertain and multimodal problem.By inputting a grayscale image into a coloring network,visually plausible colored photos can be generated.Conventional methods primarily rely on semanti...Image coloring is an inherently uncertain and multimodal problem.By inputting a grayscale image into a coloring network,visually plausible colored photos can be generated.Conventional methods primarily rely on semantic information for image colorization.These methods still suffer from color contamination and semantic confusion.This is largely due to the limited capacity of convolutional neural networks to learn deep semantic information inherent in images effectively.In this paper,we propose a network structure that addresses these limitations by leveraging multi-level semantic information classification and fusion.Additionally,we introduce a global semantic fusion network to combat the issues of color contamination.The proposed coloring encoder accurately extracts object-level semantic information from images.To further enhance visual plausibility,we employ a self-supervised adversarial training method.We train the network structure on various datasets with varying amounts of data and evaluate its performance using the ImageNet validation set and COCO validation set.Experimental results demonstrate that our proposed algorithm can generate more realistic images compared to previous approaches,showcasing its high generalization ability.展开更多
The destabilization of overhanging rock is a dangerous geological problem.In this study,a generalized model of typical overhanging cliffs from the Three Gorges Reservoir area in China with different fracture angles,fr...The destabilization of overhanging rock is a dangerous geological problem.In this study,a generalized model of typical overhanging cliffs from the Three Gorges Reservoir area in China with different fracture angles,fracture lengths,and free surface depths is constructed to investigate the cracking and deformation behavior of overhanging rocks.Laboratory tests and deformation field monitoring using the digital image correlation(DIC)method are performed on these specimens to reproduce the destabilization and failure process of overhanging rock under external loading.The influence of peak load is found to be the most sensitive to the fracture length,followed by the free surface depth,and to be the least sensitive to the fracture angle.The DIC-based strain fields reveal that the fracture angle and free surface depth significantly alter the crack propagation paths,whereas the influence of the fracture length is weaker.These parameters also affect the crack initiation time.The relative displacement evolution characteristics indicate that fracture angle,fracture length,and free surface depth affect the shape and size of the rotating block,the rotation center,and the rotation pivot point and degree,respectively.The grayscale characteristic evolution trends are similar for all examined overhanging rock specimens.The evolution of the grayscale indices based on DIC can be divided into high-frequency oscillation,smooth decline(or smooth downward concavity),and stable development stages.Furthermore,the multistage properties of the indices can be used to identify the fracture state of overhanging rocks,providing a theoretical basis for graded early warning of rockfall disasters.展开更多
A two-stage driving circuit of a one-chip TFT-LCD driver IC for portable electronic devices is proposed. The driving buffers of the new circuit are built in the γ-correction circuit rather than in the source driver. ...A two-stage driving circuit of a one-chip TFT-LCD driver IC for portable electronic devices is proposed. The driving buffers of the new circuit are built in the γ-correction circuit rather than in the source driver. The power consumption,die area, and driving capability of the driving circuit are discussed in detail. For a two-stage driving circuit with 13 driving buffers, the settling time of the driving voltage within 0.2% error is about 19.2μs when 396 pixel-loads are driven by the same grayscale voltage. The quiescent current of the whole driving circuit is 518μ~A,and the power consumption can be reduced by 77%. The proposed driving circuit is successfully applied in a 132RGB × 176-dot,260k color one-chip driver IC developed by us for the TFT-LCD of mobile phone, and it can also be used in other portable electronic devices, such as PDAs and digital cameras.展开更多
A series of laboratory investigations are conducted to analyze the effect of flocculant type on the spatial morphology and microstructural characteristics of flocs during the flocculation and settling of tailings.Four...A series of laboratory investigations are conducted to analyze the effect of flocculant type on the spatial morphology and microstructural characteristics of flocs during the flocculation and settling of tailings.Four flocculant types(i.e.,ZYZ,JYC-2,ZYD,and JYC-1)are considered in this study.The fractal characteristics and internal structures of tailings flocs with different flocculant types and settlement heights are analyzed by conducting scanning electron microscopy and X-ray micro-computed tomography scanning experiments based on the fractal theory.Results show that unclassified tailings flocs are irregular clusters with fractal characteristics,and the flocculation effect of the four flocculant types has the following trend:ZYZ>JYC-2>ZYD>JYC-1.The size and average grayscale value of tailings flocs decrease with the increase in settlement height.The average grayscale values at the top and bottom are 144 and 103,respectively.The settlement height remarkably affects the pore distribution pattern,as reflected in the constructed three-dimensional pore model of tailings flocs.The top part of flocs has relatively good penetration,whereas the bottom part of flocs has mostly dispersed pores.The number of pores increases exponentially with the increase in settlement height.By contrast,the size of pores initially increases and subsequently decreases with the increase in settlement height.展开更多
Based on the "Grayscales average distribution" method which equally distributes the input gray levels to output gray levels, three improved methods named: "Reduce the gray range expressed by the less si...Based on the "Grayscales average distribution" method which equally distributes the input gray levels to output gray levels, three improved methods named: "Reduce the gray range expressed by the less significant subfields", "Low levels preset" and "Modify the exponent of inverse-gamma function" are proposed in this paper. Using these methods, the inverse-gamma relation subfields code can be obtained easily which can improve the low level expressions of AC-PDP. And a program, "gray scales distribution validate program", which can enhance the expressions of the demanded gray levels range, is also proposed in this paper.展开更多
This article introduces the application of image recognition technology in cement pavement crack detection and put forward to method fordetermining threshold about grayscale stretching. This algorithm is designed for ...This article introduces the application of image recognition technology in cement pavement crack detection and put forward to method fordetermining threshold about grayscale stretching. This algorithm is designed for binarization which has a self-adaptive characteristic. After theimage is preprocessed, we apply 2D wavelet and Laplace operator to process the image. According to the characteristic of pixel of gray image, analgorithm designed on binarization for Binary image. The feasibility of this method can be verified the image processed by comparing with theresults of three algorithms: Otsu method, iteration method and fixed threshold method.展开更多
AIM:To investigate the value of duplex Doppler ultrasonography (US) in the assessment of the hemodynamics of the portal and hepatic veins in a cohort of children with chronic liver disease (CLD) and to detect any rela...AIM:To investigate the value of duplex Doppler ultrasonography (US) in the assessment of the hemodynamics of the portal and hepatic veins in a cohort of children with chronic liver disease (CLD) and to detect any relationship between the US changes,etiology and severity (or stage) of CLD. METHODS:We prospectively enrolled 25 children with biopsy-proven CLD. Thirteen had cirrhosis (aged 8.9 ± 2.0 years) and 12 had chronic hepatitis (aged 9.3 ± 2.3 years). Gray scale and color-coded duplex Doppler US were performed for all,as well as 30 healthy age and sex-matched controls. Findings were correlated with clinical,laboratory and histopathological characteristics. RESULTS:Prominent caudate lobe was detected in 100% of cirrhotics,but none of the chronic hepatitis or controls. Thickened lesser omentum and loss of the triphasic waveform of the hepatic vein were present in 69.2% and 53.8% of cirrhotics vs 33.3% and 8.3% of chronic hepatitis respectively. Portal vein flow velocity was significantly lower (P < 0.0001) and the congestion index was significantly higher (P < 0.005) in both patient groups compared to controls. Child-Pugh's staging showed a positive correlation with both abnormal hepatic vein waveform and direction of portal blood flow; and a negative correlation with both hepatic and portal vein flow velocities. No correlation with the etiology of CLD could be detected. CONCLUSION:Duplex Doppler added to grayscale US can detect significant morphologic and portal hemodynamic changes that correlate with the severity (stage) of CLD,but not with etiology.展开更多
An intuitive method for circle fitting is proposed. Assuming an approximate circle(CA,n) for the fitting of some scattered points, it can be imagined that every point would apply a force to CA,n, which all together fo...An intuitive method for circle fitting is proposed. Assuming an approximate circle(CA,n) for the fitting of some scattered points, it can be imagined that every point would apply a force to CA,n, which all together form an overall effect that "draws" CA,n towards best fitting to the group of points. The basic element of the force is called circular attracting factor(CAF) which is defined as a real scalar in a radial direction of CA,n. An iterative algorithm based on this idea is proposed, and the convergence and accuracy are analyzed. The algorithm converges uniformly which is proved by the analysis of Lyapunov function, and the accuracy of the algorithm is in accord with that of geometric least squares of circle fitting. The algorithm is adopted to circle detection in grayscale images, in which the transferring to binary images is not required, and thus the algorithm is less sensitive to lightening and background noise. The main point for the adaption is the calculation of CAF which is extended in radial directions of CA,n for the whole image. All pixels would apply forces to CA,n, and the overall effect of forces would be equivalent to a force from the centroid of pixels to CA,n. The forces from would-be edge pixels would overweigh that from noisy pixels, so the following approximate circle would be of better fitting. To reduce the amount of calculation, pixels are only used in an annular area including the boundary of CA,n just in between for the calculation of CAF. Examples are given, showing the process of circle fitting of scattered points around a circle from an initial assuming circle, comparing the fitting results for scattered points from some related literature, applying the method proposed for circular edge detection in grayscale images with noise, and/or with only partial arc of a circle, and for circle detection in BGA inspection.展开更多
A comprehensive evaluation method is proposed to analyze dust pollution generated in the production process of mines.The method employs an optimized image-processing and deep learning framework to characterize the gra...A comprehensive evaluation method is proposed to analyze dust pollution generated in the production process of mines.The method employs an optimized image-processing and deep learning framework to characterize the gray and fractal features in dust images.The research reveals both linear and logarithmic correlations between the gray features,fractal dimension,and dust mass,while employing Chauvenel criteria and arithmetic averaging to minimize data discreteness.An integrated hazardous index is developed,including a logarithmic correlation between the index and dust mass,and a four-category dataset is subsequently prepared for the deep learning framework.Based on the range of the hazardous index,the dust images are divided into four categories.Subsequently,a dust risk classifcation system is established using the deep learning model,which exhibits a high degree of performance after the training process.Notably,the model achieves a testing accuracy of 95.3%,indicating its efectiveness in classifying diferent levels of dust pollution,and the precision,recall,and F1-score of the system confrm its reliability in analyzing dust pollution.Overall,the proposed method provides a reliable and efcient way to monitor and analyze dust pollution in mines.展开更多
基金supported by the National Natural Science Foundation of China(42122017,41821002)the Independent Innovation Research Program of China University of Petroleum(East China)(21CX06001A).
文摘It is of great significance to accurately and rapidly identify shale lithofacies in relation to the evaluation and prediction of sweet spots for shale oil and gas reservoirs.To address the problem of low resolution in logging curves,this study establishes a grayscale-phase model based on high-resolution grayscale curves using clustering analysis algorithms for shale lithofacies identification,working with the Shahejie For-mation,Bohai Bay Basin,China.The grayscale phase is defined as the sum of absolute grayscale and relative amplitude as well as their features.The absolute grayscale is the absolute magnitude of the gray values and is utilized for evaluating the material composition(mineral composition+total organic carbon)of shale,while the relative amplitude is the difference between adjacent gray values and is used to identify the shale structure type.The research results show that the grayscale phase model can identify shale lithofacies well,and the accuracy and applicability of this model were verified by the fitting relationship between absolute grayscale and shale mineral composition,as well as corresponding re-lationships between relative amplitudes and laminae development in shales.Four lithofacies are iden-tified in the target layer of the study area:massive mixed shale,laminated mixed shale,massive calcareous shale and laminated calcareous shale.This method can not only effectively characterize the material composition of shale,but also numerically characterize the development degree of shale laminae,and solve the problem that difficult to identify millimeter-scale laminae based on logging curves,which can provide technical support for shale lithofacies identification,sweet spot evaluation and prediction of complex continental lacustrine basins.
基金co-supported by China Postdoctoral Science Foundation (20090461314)
文摘Dynamic infrared scene simulation is for discovering and solving the problems encountered in designing, developing and manufacturing infrared imaging guidance weapons. The infrared scene simulation is explored by using the digital grayscale modulation method. The infrared image modulation model of a digital micro-mirror device （DMD） is established and then the infrared scene simulator prototype which is based on DMD grayscale modulation is developed. To evaluate its main parameters such as resolution, contrast, minimum temperature difference, gray scale, various DMD subsystems such as signal decoding, image normalization, synchronization drive, pulse width modulation （PWM） and DMD chips are designed. The infrared scene simulator is tested on a certain infrared missile seeker. The test results show preliminarily that the infrared scene simulator has high gray scale, small geometrical distortion and highly resolvable imaging resolution and contrast and yields high-fidelity images, thus being able to meet the requirements for the infrared scene simulation inside a laboratory.
基金supported by the National Key Research and Development Program of China(Nos.2017YFA0403801,2017YFA0206004,2018YFC1200204)the National Natural Science Foundation of China(NSFC)(Nos.81430087,11775297,U1932205).
文摘Doped elements in alloys significantly impact their performance.Conventional methods usually sputter the surface material of the sample,or their performance is limited to the surface of alloys owing to their poor penetration ability.The X-ray K-edge subtraction(KES)method exhibits great potential for the nondestructive in situ detection of element contents in alloys.However,the signal of doped elements usually deteriorates because of the strong absorption of the principal component and scattering of crystal grains.This in turn prevents the extensive application of X-ray KES imaging to alloys.In this study,methods were developed to calibrate the linearity between the grayscale of the KES image and element content.The methods were aimed at the sensitive analysis of elements in alloys.Furthermore,experiments with phantoms and alloys demonstrated that,after elaborate calibration,X-ray KES imaging is capable of nondestructive and sensitive analysis of doped elements in alloys.
基金supported by National Natural Science Foundation of China(91950114,12161141010)Zhangjiang Laboratory,Guangdong Provincial Innovation and Entrepreneurship Project(2017ZT07C071)+1 种基金Natural Science Foundation of Shenzhen Innovation Commission(JCYJ20200109140808088)K.C.would like to thank the support from Hong Kong Research Grant Council AoE/P-02/12 and 12303019.
文摘Structural color from artificial structures,due to its environmental friendliness and excellent durability,represents a route for color printing applications.Among various physical mechanisms,the Fabry–Perot(F–P)cavity effect provides a powerful way to generate vivid colors in either the reflection or transmission direction.Most of the previous F–P type color printing works rely on electron beam grayscale lithography,however,with this technique it is challenging to make large-area and low-cost devices.To circumvent this constraint,we propose to fabricate the F–P type color printing device by the laser grayscale lithography process.The F–P cavity consists of two thin silver films as mirrors and a photoresist film with a spatially variant thickness as the spacer layer.By controlling the laser exposure dose pixel by pixel,a centimeter-scale fullcolor printing device with a spatial resolution up to 5μm×5μm is demonstrated.The proposed large area color printing device may have great potential in practical application areas such as color displays,hyperspectral imaging,advanced painting,and so on.
基金The National Natural Science Foundation ofChina(No.60372076)
文摘There are many detectors for the least significant bit(LSB)steganography which is broadly used in hiding information in the digital images.The length of the hidden information is one of the most important parameters in detecting steganographic information.Using 2-D gradient of a pixel and the distance between variables the proposed method gives the length of hidden information in natural grayscale images without original image.Extensive experimental results show good performance even at low embedding rate compared with other methods.Furthermore,the proposed method also works well disregarding the status of the embedded information.
文摘This document describes the use of grayscale mapping and GIS for identification of historical irrigated lands. Historical irrigated lands form the basis for water rights—a private property right in New Mexico that is bought and sold on the open market. Identification of irrigated land on historical photography is both a science and an art. Grayscale mapping of historic black and white photographs can aid in the identification of irrigated lands. GIS allows historical images to be geo-referenced and area computations to be performed on polygons that define the irrigated lands.
基金supported by the National Natural Science Foundation of China(Nos.62331006,62171038,and 62088101)the Fundamental Research Funds for the Central Universities.
文摘Near-InfraRed(NIR)imaging technology plays a pivotal role in assisted driving and safety surveillance systems,yet its monochromatic nature and deficiency in detail limit its further application.Recent methods aim to recover the corresponding RGB image directly from the NIR image using Convolutional Neural Networks(CNN).However,these methods struggle with accurately recovering both luminance and chrominance information and the inherent deficiencies in NIR image details.In this paper,we propose grayscale-assisted RGB image restoration from NIR images to recover luminance and chrominance information in two stages.We address the complex NIR-to-RGB conversion challenge by decoupling it into two separate stages.First,it converts NIR to grayscale images,focusing on luminance learning.Then,it transforms grayscale to RGB images,concentrating on chrominance information.In addition,we incorporate frequency domain learning to shift the image processing from the spatial domain to the frequency domain,facilitating the restoration of the detailed textures often lost in NIR images.Empirical evaluations of our grayscale-assisted framework and existing state-of-the-art methods demonstrate its superior performance and yield more visually appealing results.Code is accessible at:https://github.com/Yiiclass/RING.
基金supported by the Engineering and Physical Sciences Research Council of the United Kingdom(Grant Ref:EP/M003175/1)the support from the Chinese Scholarship Council(CSC,No.201608310007).
文摘Images perceived by human eyes or recorded by cameras are usually optical patterns with spatially varying intensity or color profiles.In addition to the intensity and color,the information of an image can be encoded in a spatially varying distribution of phase or polarization state.Interestingly,such images might not be able to be directly viewed by human eyes or cameras because they may exhibit highly uniform intensity profiles.Here,we propose and experimentally demonstrate an approach to hide a high-resolution grayscale image in a square laser beam with a size of less than half a millimeter.An image with a pixel size of 300×300 nm is encoded into the spatially variant polarization states of the laser beam,which can be revealed after passing through a linear polarizer.This unique technology for hiding grayscale images and polarization manipulation provides new opportunities for various applications,including encryption,imaging,optical communications,quantum science and fundamental physics.
基金This work was supported in part by the National Natural Science Foundation of China(Grants Nos.61865010 and 61565012)in part by the China Postdoctoral Science Foundation(Grant No.2015T80691)+1 种基金in part by the Science and Technology Plan Project of Jiangxi Province(Grant No.20151BBE50092)in part by the Funding Scheme to Outstanding Young Talents of Jiangxi Province(Grant No.20171BCB23007).
文摘In single-pixel imaging or computational ghost imaging,the measurement matrix has a great impact on the performance of the imaging system,because it involves modulation of the optical signal and image reconstruction.The measurement matrix reported in the existing literatures is first binarized and then loaded onto the digital micro-mirror device(DMD)for optical modulation,that is,each pixel can only be modulated into on-off states.In this paper,we propose a digital grayscale modulation method for more efficient compressive sampling.On the basis of this,we demonstrate a single photon compressive imaging system.A control and counting circuit,based on field-programmable gate array(FPGA),is developed to control DMD to conduct digital grayscale modulation and count single-photon pulse output from the photomultiplier tube(PMT)simultaneously.The experimental results show that the imaging reconstruction quality can be improved by increasing the sparsity ratio properly and compressive sampling ratio(SR)of these gray-scale matrices.However,when the compressive SR and sparsity ratio are increased appropriately to a certain value,the reconstruction quality is usually saturated,and the imaging reconstruction quality of the digital grayscale modulation is better than that of binary modulation.
文摘Background:Grayscale image attributes of computed tomography(CT)of pulmonary scans contain valuable information relating to patients with respiratory ailments.These attributes are used to evaluate the severity of lung conditions of patients confirmed to be with and without COVID-19.Method:Five hundred thirteen CT images relating to 57 patients(49 with COVID-19;8 free of COVID-19)were collected at Namazi Medical Centre(Shiraz,Iran)in 2020 and 2021.Five visual scores(VS:0,1,2,3,or 4)are clinically assigned to these images with the score increasing with the severity of COVID-19-related lung conditions.Eleven deep learning and machine learning techniques(DL/ML)are used to distinguish the VS class based on 12 grayscale image attributes.Results:The convolutional neural network achieves 96.49%VS accuracy(18 errors from 513 images)successfully distinguishing VS Classes 0 and 1,outperforming clinicians’visual inspections.An algorithmic score(AS),involving just five grayscale image attributes,is developed independently of clinicians’assessments(99.81%AS accuracy;1 error from 513 images).Conclusion:Grayscale CT image attributes can be successfully used to distinguish the severity of COVID-19 lung damage.The AS technique developed provides a suitable basis for an automated system using ML/DL methods and 12 image attributes.
基金supported by the Key Research and Development Program of Shanxi Province(202102030201002)the Changjiang Scholars and Innovative Research Team at the University of Ministry of Education of China(IRT_17R70)+2 种基金the State Key Program of National Natural Science of China(11434007)the 111 Project(D18001)the Fund for Shanxi“1331 Project”Key Subjects Construction.
文摘Achieving a high sensitivity for practical applications has always been one of the main developmental directions for wearable flexible pressure sensors.This paper introduces a laser speckle grayscale lithography system and a novel method for fabricating random conical array microstructures using grainy laser speckle patterns.Its feasibility is attributed to the autocorrelation function of the laser speckle intensity,which adheres to a first-order Bessel function of the first kind.Through objective speckle size and exposure dose manipulations,we developed a microstructured photoresist with various micromorphologies.These microstructures were used to form polydimethylsiloxane microstructured electrodes that were used in flexible capacitive pressure sensors.These-1 sensors exhibited an ultra-high sensitivity:19.76 kPa for the low-pressure range of 0-100 Pa.Their minimum detection threshold was 1.9 Pa,and they maintained stability and resilience over 10,000 test cycles.These sensors proved to be adept at capturing physiological signals and providing tactile feedback,thereby emphasizing their practical value.
基金supported by the Key Technologies R&D Program of Tianjin(Nos.24YFZCSN00030 and 24YFYSHZ00090)。
文摘Image coloring is an inherently uncertain and multimodal problem.By inputting a grayscale image into a coloring network,visually plausible colored photos can be generated.Conventional methods primarily rely on semantic information for image colorization.These methods still suffer from color contamination and semantic confusion.This is largely due to the limited capacity of convolutional neural networks to learn deep semantic information inherent in images effectively.In this paper,we propose a network structure that addresses these limitations by leveraging multi-level semantic information classification and fusion.Additionally,we introduce a global semantic fusion network to combat the issues of color contamination.The proposed coloring encoder accurately extracts object-level semantic information from images.To further enhance visual plausibility,we employ a self-supervised adversarial training method.We train the network structure on various datasets with varying amounts of data and evaluate its performance using the ImageNet validation set and COCO validation set.Experimental results demonstrate that our proposed algorithm can generate more realistic images compared to previous approaches,showcasing its high generalization ability.
基金supported by the China National Natural Science Foundation(Grant No.42362034)the Applied Basic Research Foundation of Yunnan Province,China(Grant No.202401AS070068).
文摘The destabilization of overhanging rock is a dangerous geological problem.In this study,a generalized model of typical overhanging cliffs from the Three Gorges Reservoir area in China with different fracture angles,fracture lengths,and free surface depths is constructed to investigate the cracking and deformation behavior of overhanging rocks.Laboratory tests and deformation field monitoring using the digital image correlation(DIC)method are performed on these specimens to reproduce the destabilization and failure process of overhanging rock under external loading.The influence of peak load is found to be the most sensitive to the fracture length,followed by the free surface depth,and to be the least sensitive to the fracture angle.The DIC-based strain fields reveal that the fracture angle and free surface depth significantly alter the crack propagation paths,whereas the influence of the fracture length is weaker.These parameters also affect the crack initiation time.The relative displacement evolution characteristics indicate that fracture angle,fracture length,and free surface depth affect the shape and size of the rotating block,the rotation center,and the rotation pivot point and degree,respectively.The grayscale characteristic evolution trends are similar for all examined overhanging rock specimens.The evolution of the grayscale indices based on DIC can be divided into high-frequency oscillation,smooth decline(or smooth downward concavity),and stable development stages.Furthermore,the multistage properties of the indices can be used to identify the fracture state of overhanging rocks,providing a theoretical basis for graded early warning of rockfall disasters.
文摘A two-stage driving circuit of a one-chip TFT-LCD driver IC for portable electronic devices is proposed. The driving buffers of the new circuit are built in the γ-correction circuit rather than in the source driver. The power consumption,die area, and driving capability of the driving circuit are discussed in detail. For a two-stage driving circuit with 13 driving buffers, the settling time of the driving voltage within 0.2% error is about 19.2μs when 396 pixel-loads are driven by the same grayscale voltage. The quiescent current of the whole driving circuit is 518μ~A,and the power consumption can be reduced by 77%. The proposed driving circuit is successfully applied in a 132RGB × 176-dot,260k color one-chip driver IC developed by us for the TFT-LCD of mobile phone, and it can also be used in other portable electronic devices, such as PDAs and digital cameras.
基金This work was financially supported by the National Natural Science Foundation of China(Nos.51974012 and 51804017)the National Key Research and Development Program of China(No.2018YFC0604602)+1 种基金the Fundamental Research Funds for the Central Universities,China(No.FRF-BD-19-005A)the Opening Fund of State Key Laboratory of Nonlinear Mechanics(No.LNM202009).
文摘A series of laboratory investigations are conducted to analyze the effect of flocculant type on the spatial morphology and microstructural characteristics of flocs during the flocculation and settling of tailings.Four flocculant types(i.e.,ZYZ,JYC-2,ZYD,and JYC-1)are considered in this study.The fractal characteristics and internal structures of tailings flocs with different flocculant types and settlement heights are analyzed by conducting scanning electron microscopy and X-ray micro-computed tomography scanning experiments based on the fractal theory.Results show that unclassified tailings flocs are irregular clusters with fractal characteristics,and the flocculation effect of the four flocculant types has the following trend:ZYZ>JYC-2>ZYD>JYC-1.The size and average grayscale value of tailings flocs decrease with the increase in settlement height.The average grayscale values at the top and bottom are 144 and 103,respectively.The settlement height remarkably affects the pore distribution pattern,as reflected in the constructed three-dimensional pore model of tailings flocs.The top part of flocs has relatively good penetration,whereas the bottom part of flocs has mostly dispersed pores.The number of pores increases exponentially with the increase in settlement height.By contrast,the size of pores initially increases and subsequently decreases with the increase in settlement height.
文摘Based on the "Grayscales average distribution" method which equally distributes the input gray levels to output gray levels, three improved methods named: "Reduce the gray range expressed by the less significant subfields", "Low levels preset" and "Modify the exponent of inverse-gamma function" are proposed in this paper. Using these methods, the inverse-gamma relation subfields code can be obtained easily which can improve the low level expressions of AC-PDP. And a program, "gray scales distribution validate program", which can enhance the expressions of the demanded gray levels range, is also proposed in this paper.
文摘This article introduces the application of image recognition technology in cement pavement crack detection and put forward to method fordetermining threshold about grayscale stretching. This algorithm is designed for binarization which has a self-adaptive characteristic. After theimage is preprocessed, we apply 2D wavelet and Laplace operator to process the image. According to the characteristic of pixel of gray image, analgorithm designed on binarization for Binary image. The feasibility of this method can be verified the image processed by comparing with theresults of three algorithms: Otsu method, iteration method and fixed threshold method.
基金Supported by Cairo University, as six of the researchers are employees of that University
文摘AIM:To investigate the value of duplex Doppler ultrasonography (US) in the assessment of the hemodynamics of the portal and hepatic veins in a cohort of children with chronic liver disease (CLD) and to detect any relationship between the US changes,etiology and severity (or stage) of CLD. METHODS:We prospectively enrolled 25 children with biopsy-proven CLD. Thirteen had cirrhosis (aged 8.9 ± 2.0 years) and 12 had chronic hepatitis (aged 9.3 ± 2.3 years). Gray scale and color-coded duplex Doppler US were performed for all,as well as 30 healthy age and sex-matched controls. Findings were correlated with clinical,laboratory and histopathological characteristics. RESULTS:Prominent caudate lobe was detected in 100% of cirrhotics,but none of the chronic hepatitis or controls. Thickened lesser omentum and loss of the triphasic waveform of the hepatic vein were present in 69.2% and 53.8% of cirrhotics vs 33.3% and 8.3% of chronic hepatitis respectively. Portal vein flow velocity was significantly lower (P < 0.0001) and the congestion index was significantly higher (P < 0.005) in both patient groups compared to controls. Child-Pugh's staging showed a positive correlation with both abnormal hepatic vein waveform and direction of portal blood flow; and a negative correlation with both hepatic and portal vein flow velocities. No correlation with the etiology of CLD could be detected. CONCLUSION:Duplex Doppler added to grayscale US can detect significant morphologic and portal hemodynamic changes that correlate with the severity (stage) of CLD,but not with etiology.
基金Project(2013CB035504) supported by the National Basic Research Program of ChinaProject(2012zzts078) supported by the Fundamental Research Funds for the Central Universities of Central South University,ChinaProject(2009ZX02038) supported by the National Science and Technology Major Project of the Ministry of Science and Technology of China
文摘An intuitive method for circle fitting is proposed. Assuming an approximate circle(CA,n) for the fitting of some scattered points, it can be imagined that every point would apply a force to CA,n, which all together form an overall effect that "draws" CA,n towards best fitting to the group of points. The basic element of the force is called circular attracting factor(CAF) which is defined as a real scalar in a radial direction of CA,n. An iterative algorithm based on this idea is proposed, and the convergence and accuracy are analyzed. The algorithm converges uniformly which is proved by the analysis of Lyapunov function, and the accuracy of the algorithm is in accord with that of geometric least squares of circle fitting. The algorithm is adopted to circle detection in grayscale images, in which the transferring to binary images is not required, and thus the algorithm is less sensitive to lightening and background noise. The main point for the adaption is the calculation of CAF which is extended in radial directions of CA,n for the whole image. All pixels would apply forces to CA,n, and the overall effect of forces would be equivalent to a force from the centroid of pixels to CA,n. The forces from would-be edge pixels would overweigh that from noisy pixels, so the following approximate circle would be of better fitting. To reduce the amount of calculation, pixels are only used in an annular area including the boundary of CA,n just in between for the calculation of CAF. Examples are given, showing the process of circle fitting of scattered points around a circle from an initial assuming circle, comparing the fitting results for scattered points from some related literature, applying the method proposed for circular edge detection in grayscale images with noise, and/or with only partial arc of a circle, and for circle detection in BGA inspection.
基金supported by the National Natural Science Foundation of China(52174099)the Natural Science Foundation of Liaoning Province(2021-KF-23-01)the Fundamental Research Funds for the Central Universities of Central South University(2022ZZTS0510).
文摘A comprehensive evaluation method is proposed to analyze dust pollution generated in the production process of mines.The method employs an optimized image-processing and deep learning framework to characterize the gray and fractal features in dust images.The research reveals both linear and logarithmic correlations between the gray features,fractal dimension,and dust mass,while employing Chauvenel criteria and arithmetic averaging to minimize data discreteness.An integrated hazardous index is developed,including a logarithmic correlation between the index and dust mass,and a four-category dataset is subsequently prepared for the deep learning framework.Based on the range of the hazardous index,the dust images are divided into four categories.Subsequently,a dust risk classifcation system is established using the deep learning model,which exhibits a high degree of performance after the training process.Notably,the model achieves a testing accuracy of 95.3%,indicating its efectiveness in classifying diferent levels of dust pollution,and the precision,recall,and F1-score of the system confrm its reliability in analyzing dust pollution.Overall,the proposed method provides a reliable and efcient way to monitor and analyze dust pollution in mines.
