Accurate three-dimensional （3D） target positioning is of great importance in many industrial applications. Although various methods for reconstructing 3D information from a set of images have been available in the l...Accurate three-dimensional （3D） target positioning is of great importance in many industrial applications. Although various methods for reconstructing 3D information from a set of images have been available in the literature, few of them pay enough attention to the indispensable procedures, such as target extraction from images and image correction having strong influences upon the 3D positioning accuracy. This article puts forward a high-precision ellipse center （target point） extraction method and a new image correction approach which has been integrated into the 3D reconstruction pipeline with a concise implicit model to accurately compensates for the image distortion. The methods are applied to a copyright-reserved close range photogrammetric system. Real measuring experiments and industrial applications have evidenced the proposed methods, which can significantly improve the 3D positioning accuracy.展开更多
A method based on multiple images captured under different light sources at different incident angles was developed to recognize the coal density range in this study.The innovation is that two new images were construc...A method based on multiple images captured under different light sources at different incident angles was developed to recognize the coal density range in this study.The innovation is that two new images were constructed based on images captured under four single light sources.Reconstruction image 1 was constructed by fusing greyscale versions of the original images into one image,and Reconstruction image2 was constructed based on the differences between the images captured under the different light sources.Subsequently,the four original images and two reconstructed images were input into the convolutional neural network AlexNet to recognize the density range in three cases:-1.5(clean coal) and+1.5 g/cm^(3)(non-clean coal);-1.8(non-gangue) and+1.8 g/cm^(3)(gangue);-1.5(clean coal),1.5-1.8(middlings),and+1.8 g/cm^(3)(gangue).The results show the following:(1) The reconstructed images,especially Reconstruction image 2,can effectively improve the recognition accuracy for the coal density range compared with images captured under single light source.(2) The recognition accuracies for gangue and non-gangue,clean coal and non-clean coal,and clean coal,middlings,and gangue reached88.44%,86.72% and 77.08%,respectively.(3) The recognition accuracy increases as the density moves further away from the boundary density.展开更多
Research on the range anomaly suppression algorithm in laser radar （ladar） range images is significant in the application and development of ladar. But most of existing algorithms cannot protect the edge and linear ...Research on the range anomaly suppression algorithm in laser radar （ladar） range images is significant in the application and development of ladar. But most of existing algorithms cannot protect the edge and linear target well while suppressing the range anomaly. Aiming at this problem, the differences among the edge, linear target, and range anomaly are analyzed and a novel algo- rithm based on neighborhood pixels detection is proposed. Firstly, the range differences between current pixel and its neighborhood pixels are calculated. Then, the number of neighborhood pixels is detected by the range difference threshold. Finally, whether the current pixel is a range anomaly is distinguished by the neighbor- hood pixel number threshold. Experimental results show that the new algorithm not only has a better range anomaly suppression performance and higher efficiency, but also protects the edge and linear target preferably compared with other algorithms.展开更多
The traditional Range Doppler(RD)algorithm is unable to meet practical needs owing to the limit of resolution.The order of fractional Fourier Transform(FrFT)and the length of sampling signals affect SAR imaging perfor...The traditional Range Doppler(RD)algorithm is unable to meet practical needs owing to the limit of resolution.The order of fractional Fourier Transform(FrFT)and the length of sampling signals affect SAR imaging performance when FrFT is applied to RD algorithm.To overcome the above shortcomings,the purpose of this paper is to propose a high-resolution SAR image algorithm by using the optimal order of FrFT and the sample length constraints for the range direction.The expression of the optimal order of SAR range signals via FrFT is deduced in detail.The initial sample length and its constraints are proposed to obtain the best sample length of SAR range signals.Experimental results demonstrate that,when the range sampling-length changes in a certain interval,the best sampling-length will be obtained,which the best values of the range resolution,PSLR and ISLR,will be derived respectively.Compared with traditional RD algorithm,the main-lobe width of the peak-point target of the proposed algorithm is narrow in the range direction.While the peak amplitude of the first side-lobe is reduced significantly,those of other side-lobes also drop in various degrees.展开更多
This paper presents an unsupervised range image segmentation based on Kohonen neural network. At first, the derivative and partial derivative of each point are calculated and the normal in each points is gotten. With ...This paper presents an unsupervised range image segmentation based on Kohonen neural network. At first, the derivative and partial derivative of each point are calculated and the normal in each points is gotten. With the character vectors including normal and range value, self-organization map is introduced to cluster. The normal analysis is used to eliminate over-segmentation and the last result is gotten. This method avoid selecting original seeds and uses fewer samples, moreover computes rapidly. The experiment shows the better performance.展开更多
This paper presents an algorithm for registering multiple range images, which is efficient and robust in the presence of noise and occlusion. The registration algorithm is an integration of the iterative closest point...This paper presents an algorithm for registering multiple range images, which is efficient and robust in the presence of noise and occlusion. The registration algorithm is an integration of the iterative closest point(ICP) algorithm with random sampling and least squares(LS) estimator. It iterates the processes of random sampling with conditional reject, estimation of motion parameters by using ICP algorithm and evaluation of the estimation. The algorithm first creates an octree spline of object surface to quickly compute point to surface distance and its closest point using trilinear interpolation. The advantages of the proposed method are the reduction of computational cost and robustness to outliers.展开更多
Distortion-free data embedding is a technique which can assure that not only the secret data is correctly extracted but also the cover media is recovered without any distortion after secret data is extracted completel...Distortion-free data embedding is a technique which can assure that not only the secret data is correctly extracted but also the cover media is recovered without any distortion after secret data is extracted completely. Because of these advantages, this technique attracts the attention of many researchers. In this paper, a new distortion-free data embedding scheme for high dynamic range （HDR） images is proposed. By depending on Cartesian product, this scheme can obtain higher embedding capacity while maintaining the exactly identical cover image and stego image when using the tone mapping algorithms. In experimental results, the proposed scheme is superior to Yu et aL＇s scheme in regard to the embedding rate——an average embedding rate of 0.1355 bpp compared with Yn et aL＇s scheme （0.1270 bpp）.展开更多
The paper addresses range image segmentation, particularly of data recorded by range cameras, such as the Microsoft Kinect and the Mesa Swissranger SR4000. These devices record range images at video frame rates and al...The paper addresses range image segmentation, particularly of data recorded by range cameras, such as the Microsoft Kinect and the Mesa Swissranger SR4000. These devices record range images at video frame rates and allow for acquisition of 3-dimensional measurement sequences that can be used for 3D reconstruction of indoor environments from moving platforms. The role of segmentation is twofold. First the necessary image co-registration can be based on corresponding segments, instead of corresponding point features (which is common practice currently). Secondly, the segments can be used during subsequent object modelling. By realisising that planar regions in disparity images can be modelled as linear functions of the image coordinates, having integer values for both domain and range, the paper introduces a lookup table based implementation of local Hough transform, allowing to obtain good segmentation results at high speeds.展开更多
In this paper,a new integrated registration algorithm based on neural network and ICP(iterative closest point)algorithm is presented.A coarse registration process is implemented with neural network,and then further op...In this paper,a new integrated registration algorithm based on neural network and ICP(iterative closest point)algorithm is presented.A coarse registration process is implemented with neural network,and then further optimized by ICP algorithm.The corresponding point pairs are found according to the target points'curvature and color information.Mahalanobis distance,which reflects the scattering degree of point data,is employed to define the closest distance and the closest points.The results of the experiment show that our algorithm has better feasibility,validity and efficiency than the traditional ICP method.展开更多
An effective method for object shape recovery using HDRIs （high dynamic range images） is proposed. The radiance values of each point on the reference sphere and target object are firstly calculated, thus the set of ...An effective method for object shape recovery using HDRIs （high dynamic range images） is proposed. The radiance values of each point on the reference sphere and target object are firstly calculated, thus the set of candidate normals of each target point are found by comparing its radiance to that of each reference sphere point. In single-image shape recovery, a smoothness operation is applied to the target normals to obtain a stable and reasonable result; while in photometric stereo, radiance vectors of reference and target objects formed due to illuminations under different fight source directions are directly compared to get the most suitable target normals. Finally, the height values can be recovered from the resulting normal field. Because diffuse and specular reflection are handled in an unified framework with radiance, our approach eliminates the limitation presented in most recovery strategies, i.e., only Lambertian model can be used. The experiment results from the real and synthesized images show the performance of our approach.展开更多
Due to the complexity and asymmetrical illumination, the images of object are difficult to be effectively segmented by some routine method. In this paper, a kind of edge detection method based on image features and ge...Due to the complexity and asymmetrical illumination, the images of object are difficult to be effectively segmented by some routine method. In this paper, a kind of edge detection method based on image features and genetic algorithms neural network for range images was proposed. Fully considering the essential difference between an edge point and a noise point, some characteristic parameters were extracted from range maps as the input nodes of the network in the algorithm. Firstly, a genetic neural network was designed and implemented. The neural network is trained by genetic algorithm, and then genetic neural network algorithm is combined with the virtue of global optimization of genetic algorithm and the virtue of parallel computation of neural network, so that this algorithm is of good global property. The experimental results show that this method can get much faster and more accurate detection results than the classical differential algorithm, and has better anti-noise performance.展开更多
The radiative hypothesis has been revisited showing other characteristics, produced by the protons used as dyes in total disagree with the ones of the Body Image that appears on the Shroud of Turin. Our investigations...The radiative hypothesis has been revisited showing other characteristics, produced by the protons used as dyes in total disagree with the ones of the Body Image that appears on the Shroud of Turin. Our investigations highlight that for the protons to reach 3.7 cm in air, the distance that measures the range of discoloration effects, must be emitted with an energy of about 1.5 MeV using Wilson and Brobeck’s empirical formula and 1.35 MeV using Bethe’s. This last formula provides a result closer to reality. Bethe shows that the penetration depth is greater than that calculated empirically. Such a value of proton energy (1.35 MeV) makes it possible to satisfy the discoloration effects range for the Shroud but it is incompatible with a depth of penetration in linen that is only 200 nm. Moreover, using the same subatomic particles, we obtained on the colored linen a distribution of energy represented by regression but not linear. Thus, also the possible I(z) correlation, between color intensity and body-sheet distance, which should be due to the oxidizing action of protons, does not agree with that extracted from the Shroud of Turin.展开更多
With the developpment of image fusion technology and the maturity of wavelet theory, wavelet transform with its good time-frequency characteristics stands out in the field of image fusion. On the basis of wavelet tran...With the developpment of image fusion technology and the maturity of wavelet theory, wavelet transform with its good time-frequency characteristics stands out in the field of image fusion. On the basis of wavelet transforms theory, this article proposes a high dynamic range imaging confusion method which combines with wavelet decomposition. First, perform a wavelet multi-scale decomposition to the two registered source image; then conduct wavelet inverse transform to the decomposed images. This paper focuses on the characteristics of high frequency and low frequency domain after wavelet decomposition,using different fusion methods in each of the frequency domain, finally obtain the fused image through inverse wavelet transform image reconstruction. The simulation results and evaluation index results show that, compared with other similar methods, this method is better in retaining the original image's details information, and improves the quality of fusion image.展开更多
With the development of graphic processing unit(GPU)power,it is now possible to implement geometric correction and edge blending functions on a single computer.However,the processing resources consumed by the geometri...With the development of graphic processing unit(GPU)power,it is now possible to implement geometric correction and edge blending functions on a single computer.However,the processing resources consumed by the geometric correction and edge blending phases still burden the system and slow down the main application considerably.A new platform independent scheme is proposed,minimizing the negative influence on performance.In this scheme,parameters for geometric correction and edge blending are firstly defined in an interactive way and recorded as a 32-bit high dynamic range(HDR) image,which is then used by high level shading language(HLSL) codes embedded in the main application as a lookup table,greatly reducing the computational complexity and enhancing flexibility.展开更多
Mueller matrix polarimetry(MMP)has been proven to be a powerful tool for characterizing the microstructural features of biological samples in biomedical research and clinical diagnostics.However,the traditional Muelle...Mueller matrix polarimetry(MMP)has been proven to be a powerful tool for characterizing the microstructural features of biological samples in biomedical research and clinical diagnostics.However,the traditional Mueller matrix(MM)imaging technique based on single exposure has a limited dynamic range,leading to poor polarization image quality for biological samples with signi-cant contrast variations.In this study,we propose a novel method to generate high dynamic range(HDR)MM images based on a multi-exposure fusion algorithm.By employing an optimal exposure selection strategy for transmission imaging and a multi-exposure weighted averaging strategy for backscattering imaging,the method expands the dynamic range while accurately preserving the polarization information of the samples.Experiments of sliced and bulk tissues demonstrate that the proposed method signi¯cantly suppresses the scattering noise and improves the quality of extracted polarization parameter images,especially in accurate distinction of di®erent pathological areas.These results highlight the potential of HDR MM imaging technology in extracting polarization information from complex biological samples with high resolution and contrast.展开更多
Lunar Laser Ranging has extremely high requirements for the pointing accuracy of the telescopes used.To improve its pointing accuracy and solve the problem of insufficiently accurate telescope pointing correction achi...Lunar Laser Ranging has extremely high requirements for the pointing accuracy of the telescopes used.To improve its pointing accuracy and solve the problem of insufficiently accurate telescope pointing correction achieved by tracking stars in the all-sky region,we propose a processing scheme to select larger-sized lunar craters near the Lunar Corner Cube Retroreflector as reference features for telescope pointing bias computation.Accurately determining the position of the craters in the images is crucial for calculating the pointing bias;therefore,we propose a method for accurately calculating the crater position based on lunar surface feature matching.This method uses matched feature points obtained from image feature matching,using a deep learning method to solve the image transformation matrix.The known position of a crater in a reference image is mapped using this matrix to calculate the crater position in the target image.We validate this method using craters near the Lunar Corner Cube Retroreflectors of Apollo 15 and Luna 17 and find that the calculated position of a crater on the target image falls on the center of the crater,even for image features with large distortion near the lunar limb.The maximum image matching error is approximately 1″,and the minimum is only 0.47″,which meets the pointing requirements of Lunar Laser Ranging.This method provides a new technical means for the high-precision pointing bias calculation of the Lunar Laser Ranging system.展开更多
Aiming at the reference range selection for different antennas in interferometric inverse synthetic aperture radar （InlSAR） systems, this paper proposes a respective focusing （RF） method. The reference ranges for ...Aiming at the reference range selection for different antennas in interferometric inverse synthetic aperture radar （InlSAR） systems, this paper proposes a respective focusing （RF） method. The reference ranges for echoes of different antennas are selected respectively for RF, which is different from the traditional uniform focusing （UF） with the same reference range applied to all the antennas. First, a comparison between UF and RF for InlSAR signal model considering the ranging error is given. Compared with RF, UF has an advantage in overcoming the ranging error differences between different antennas. Then the influence of ranging error upon the interferometric imaging with RF is investigated particularly, and it is found that the ranging error differences between different antennas are far smaller than the wavelength, which is advantageous to imaging. By comparing the capabilities of inter- ferometric imaging between RF and UF, it is concluded that RF is a better choice in conquering problems such as image mismatching and phase ambiguity even with ranging errors. Simulations demonstrate the validity of the proposed method.展开更多
The range accuracy of three-dimensional（3D） ghost imaging is derived. Based on the derived range accuracy equation, the relationship between the slicing number and the range accuracy is analyzed and an optimum slici...The range accuracy of three-dimensional（3D） ghost imaging is derived. Based on the derived range accuracy equation, the relationship between the slicing number and the range accuracy is analyzed and an optimum slicing number（OSN）is determined. According to the OSN, an improved 3D ghost imaging algorithm is proposed to increase the range accuracy. Experimental results indicate that the slicing number can affect the range accuracy significantly and the highest range accuracy can be achieved if the 3D ghost imaging system works with OSN.展开更多
The ultraviolet (UV) photoresponses of Wurtzite GaN, ZnO, and 6H-SiC-based Optical Field Effect Transistor (OPFET) detectors are estimated with an in-depth analysis of the same considering the generalized model and th...The ultraviolet (UV) photoresponses of Wurtzite GaN, ZnO, and 6H-SiC-based Optical Field Effect Transistor (OPFET) detectors are estimated with an in-depth analysis of the same considering the generalized model and the front-illuminated model for high resolution imaging and UV communication applications. The gate materials considered for the proposed study are gold (Au) and Indium-Tin-Oxide (ITO) for GaN, Au for SiC, and Au and silver dioxide (AgO2) for ZnO. The results indicate significant improvement in the Linear Dynamic Range (LDR) over the previously investigated GaN OPFET (buried-gate, front-illuminated and generalized) models with Au gate. The generalized model has superior dynamic range than the front-illuminated model. In terms of responsivity, all the models including buried-gate OPFET exhibit high and comparable photoresponses. Buried-gate devices on the whole, exhibit faster response than the surface gate models except in the AgO2-ZnO generalized OPFET model wherein the switching time is the lowest. The generalized model enables faster switching than the front-illuminated model. The switching times in all the cases are of the order of nanoseconds to picoseconds. The SiC generalized OPFET model shows the highest 3-dB bandwidths of 11.88 GHz, 36.2 GHz, and 364 GHz, and modest unity-gain cut-off frequencies of 4.62 GHz, 8.71 GHz, and 5.71 GHz at the optical power densities of 0.575 μW/cm2, 0.575 mW/cm2, and 0.575 W/cm2 respectively. These are in overall, the highest detection-cum-amplifi-cation bandwidths among all the investigated devices. The same device exhibits the highest LDR of 73.3 dB. The device performance is superior to most of the other existing detectors along with comparable LDR, thus, emerging as a high performance photodetector for imaging and communication applications. All the detectors show considerably high detectivities owing to the high responsivity values. The results have been analyzed by the photovoltaic and the photoconductive effects, and the series resistance effects and will aid in conducting further research. The results are in line with the experiments and the commercially available software simulations. The devices will greatly contribute towards single photon counting, high resolution imaging, and UV communication applications.展开更多
Three dimensional(3-D)imaging algorithms with irregular planar multiple-input-multiple-output(MIMO)arrays are discussed and compared with each other.Based on the same MIMO array,a modified back projection algorithm(MB...Three dimensional(3-D)imaging algorithms with irregular planar multiple-input-multiple-output(MIMO)arrays are discussed and compared with each other.Based on the same MIMO array,a modified back projection algorithm(MBPA)is accordingly proposed and four imaging algorithms are used for comparison,back-projection method(BP),back-projection one in time domain(BP-TD),modified back-projection one and fast Fourier transform(FFT)-based MIMO range migration algorithm(FFT-based MIMO RMA).All of the algorithms have been implemented in practical application scenarios by use of the proposed imaging system.Back to the practical applications,MIMO array-based imaging system with wide-bandwidth properties provides an efficient tool to detect objects hidden behind a wall.An MIMO imaging radar system,composed of a vector network analyzer(VNA),a set of switches,and an array of Vivaldi antennas,have been designed,fabricated,and tested.Then,these algorithms have been applied to measured data collected in different scenarios constituted by five metallic spheres in the absence and in the presence of a wall between the antennas and the targets in simulation and pliers in free space for experimental test.Finally,the focusing properties and time consumption of the above algorithms are compared.展开更多
基金National Natural Science Foundation of China （50875 130） Doctoral Discipline Foundation of China （200802870016） Science Foundation of Jiangsu, China （BE2008136）
文摘Accurate three-dimensional （3D） target positioning is of great importance in many industrial applications. Although various methods for reconstructing 3D information from a set of images have been available in the literature, few of them pay enough attention to the indispensable procedures, such as target extraction from images and image correction having strong influences upon the 3D positioning accuracy. This article puts forward a high-precision ellipse center （target point） extraction method and a new image correction approach which has been integrated into the 3D reconstruction pipeline with a concise implicit model to accurately compensates for the image distortion. The methods are applied to a copyright-reserved close range photogrammetric system. Real measuring experiments and industrial applications have evidenced the proposed methods, which can significantly improve the 3D positioning accuracy.
文摘A method based on multiple images captured under different light sources at different incident angles was developed to recognize the coal density range in this study.The innovation is that two new images were constructed based on images captured under four single light sources.Reconstruction image 1 was constructed by fusing greyscale versions of the original images into one image,and Reconstruction image2 was constructed based on the differences between the images captured under the different light sources.Subsequently,the four original images and two reconstructed images were input into the convolutional neural network AlexNet to recognize the density range in three cases:-1.5(clean coal) and+1.5 g/cm^(3)(non-clean coal);-1.8(non-gangue) and+1.8 g/cm^(3)(gangue);-1.5(clean coal),1.5-1.8(middlings),and+1.8 g/cm^(3)(gangue).The results show the following:(1) The reconstructed images,especially Reconstruction image 2,can effectively improve the recognition accuracy for the coal density range compared with images captured under single light source.(2) The recognition accuracies for gangue and non-gangue,clean coal and non-clean coal,and clean coal,middlings,and gangue reached88.44%,86.72% and 77.08%,respectively.(3) The recognition accuracy increases as the density moves further away from the boundary density.
文摘Research on the range anomaly suppression algorithm in laser radar （ladar） range images is significant in the application and development of ladar. But most of existing algorithms cannot protect the edge and linear target well while suppressing the range anomaly. Aiming at this problem, the differences among the edge, linear target, and range anomaly are analyzed and a novel algo- rithm based on neighborhood pixels detection is proposed. Firstly, the range differences between current pixel and its neighborhood pixels are calculated. Then, the number of neighborhood pixels is detected by the range difference threshold. Finally, whether the current pixel is a range anomaly is distinguished by the neighbor- hood pixel number threshold. Experimental results show that the new algorithm not only has a better range anomaly suppression performance and higher efficiency, but also protects the edge and linear target preferably compared with other algorithms.
基金This work is supported by the 13th Five-Year Plan for Jiangsu Education Science(D/2020/01/22)JSPIGKZ and Natural Science Research Projects of Colleges and Universities in Jiangsu Province(19KJB510022)。
文摘The traditional Range Doppler(RD)algorithm is unable to meet practical needs owing to the limit of resolution.The order of fractional Fourier Transform(FrFT)and the length of sampling signals affect SAR imaging performance when FrFT is applied to RD algorithm.To overcome the above shortcomings,the purpose of this paper is to propose a high-resolution SAR image algorithm by using the optimal order of FrFT and the sample length constraints for the range direction.The expression of the optimal order of SAR range signals via FrFT is deduced in detail.The initial sample length and its constraints are proposed to obtain the best sample length of SAR range signals.Experimental results demonstrate that,when the range sampling-length changes in a certain interval,the best sampling-length will be obtained,which the best values of the range resolution,PSLR and ISLR,will be derived respectively.Compared with traditional RD algorithm,the main-lobe width of the peak-point target of the proposed algorithm is narrow in the range direction.While the peak amplitude of the first side-lobe is reduced significantly,those of other side-lobes also drop in various degrees.
文摘This paper presents an unsupervised range image segmentation based on Kohonen neural network. At first, the derivative and partial derivative of each point are calculated and the normal in each points is gotten. With the character vectors including normal and range value, self-organization map is introduced to cluster. The normal analysis is used to eliminate over-segmentation and the last result is gotten. This method avoid selecting original seeds and uses fewer samples, moreover computes rapidly. The experiment shows the better performance.
文摘This paper presents an algorithm for registering multiple range images, which is efficient and robust in the presence of noise and occlusion. The registration algorithm is an integration of the iterative closest point(ICP) algorithm with random sampling and least squares(LS) estimator. It iterates the processes of random sampling with conditional reject, estimation of motion parameters by using ICP algorithm and evaluation of the estimation. The algorithm first creates an octree spline of object surface to quickly compute point to surface distance and its closest point using trilinear interpolation. The advantages of the proposed method are the reduction of computational cost and robustness to outliers.
文摘Distortion-free data embedding is a technique which can assure that not only the secret data is correctly extracted but also the cover media is recovered without any distortion after secret data is extracted completely. Because of these advantages, this technique attracts the attention of many researchers. In this paper, a new distortion-free data embedding scheme for high dynamic range （HDR） images is proposed. By depending on Cartesian product, this scheme can obtain higher embedding capacity while maintaining the exactly identical cover image and stego image when using the tone mapping algorithms. In experimental results, the proposed scheme is superior to Yu et aL＇s scheme in regard to the embedding rate——an average embedding rate of 0.1355 bpp compared with Yn et aL＇s scheme （0.1270 bpp）.
文摘The paper addresses range image segmentation, particularly of data recorded by range cameras, such as the Microsoft Kinect and the Mesa Swissranger SR4000. These devices record range images at video frame rates and allow for acquisition of 3-dimensional measurement sequences that can be used for 3D reconstruction of indoor environments from moving platforms. The role of segmentation is twofold. First the necessary image co-registration can be based on corresponding segments, instead of corresponding point features (which is common practice currently). Secondly, the segments can be used during subsequent object modelling. By realisising that planar regions in disparity images can be modelled as linear functions of the image coordinates, having integer values for both domain and range, the paper introduces a lookup table based implementation of local Hough transform, allowing to obtain good segmentation results at high speeds.
基金Supported by the National Natural Science Foundation of China(69775022)
文摘In this paper,a new integrated registration algorithm based on neural network and ICP(iterative closest point)algorithm is presented.A coarse registration process is implemented with neural network,and then further optimized by ICP algorithm.The corresponding point pairs are found according to the target points'curvature and color information.Mahalanobis distance,which reflects the scattering degree of point data,is employed to define the closest distance and the closest points.The results of the experiment show that our algorithm has better feasibility,validity and efficiency than the traditional ICP method.
基金the National Basic Research Program of China(No.2006CB303105)
文摘An effective method for object shape recovery using HDRIs （high dynamic range images） is proposed. The radiance values of each point on the reference sphere and target object are firstly calculated, thus the set of candidate normals of each target point are found by comparing its radiance to that of each reference sphere point. In single-image shape recovery, a smoothness operation is applied to the target normals to obtain a stable and reasonable result; while in photometric stereo, radiance vectors of reference and target objects formed due to illuminations under different fight source directions are directly compared to get the most suitable target normals. Finally, the height values can be recovered from the resulting normal field. Because diffuse and specular reflection are handled in an unified framework with radiance, our approach eliminates the limitation presented in most recovery strategies, i.e., only Lambertian model can be used. The experiment results from the real and synthesized images show the performance of our approach.
文摘Due to the complexity and asymmetrical illumination, the images of object are difficult to be effectively segmented by some routine method. In this paper, a kind of edge detection method based on image features and genetic algorithms neural network for range images was proposed. Fully considering the essential difference between an edge point and a noise point, some characteristic parameters were extracted from range maps as the input nodes of the network in the algorithm. Firstly, a genetic neural network was designed and implemented. The neural network is trained by genetic algorithm, and then genetic neural network algorithm is combined with the virtue of global optimization of genetic algorithm and the virtue of parallel computation of neural network, so that this algorithm is of good global property. The experimental results show that this method can get much faster and more accurate detection results than the classical differential algorithm, and has better anti-noise performance.
文摘The radiative hypothesis has been revisited showing other characteristics, produced by the protons used as dyes in total disagree with the ones of the Body Image that appears on the Shroud of Turin. Our investigations highlight that for the protons to reach 3.7 cm in air, the distance that measures the range of discoloration effects, must be emitted with an energy of about 1.5 MeV using Wilson and Brobeck’s empirical formula and 1.35 MeV using Bethe’s. This last formula provides a result closer to reality. Bethe shows that the penetration depth is greater than that calculated empirically. Such a value of proton energy (1.35 MeV) makes it possible to satisfy the discoloration effects range for the Shroud but it is incompatible with a depth of penetration in linen that is only 200 nm. Moreover, using the same subatomic particles, we obtained on the colored linen a distribution of energy represented by regression but not linear. Thus, also the possible I(z) correlation, between color intensity and body-sheet distance, which should be due to the oxidizing action of protons, does not agree with that extracted from the Shroud of Turin.
文摘With the developpment of image fusion technology and the maturity of wavelet theory, wavelet transform with its good time-frequency characteristics stands out in the field of image fusion. On the basis of wavelet transforms theory, this article proposes a high dynamic range imaging confusion method which combines with wavelet decomposition. First, perform a wavelet multi-scale decomposition to the two registered source image; then conduct wavelet inverse transform to the decomposed images. This paper focuses on the characteristics of high frequency and low frequency domain after wavelet decomposition,using different fusion methods in each of the frequency domain, finally obtain the fused image through inverse wavelet transform image reconstruction. The simulation results and evaluation index results show that, compared with other similar methods, this method is better in retaining the original image's details information, and improves the quality of fusion image.
文摘With the development of graphic processing unit(GPU)power,it is now possible to implement geometric correction and edge blending functions on a single computer.However,the processing resources consumed by the geometric correction and edge blending phases still burden the system and slow down the main application considerably.A new platform independent scheme is proposed,minimizing the negative influence on performance.In this scheme,parameters for geometric correction and edge blending are firstly defined in an interactive way and recorded as a 32-bit high dynamic range(HDR) image,which is then used by high level shading language(HLSL) codes embedded in the main application as a lookup table,greatly reducing the computational complexity and enhancing flexibility.
基金supported by the Cross-research Innovation Fund of the International Graduate School at Shenzhen,Tsinghua University(JC2021002).
文摘Mueller matrix polarimetry(MMP)has been proven to be a powerful tool for characterizing the microstructural features of biological samples in biomedical research and clinical diagnostics.However,the traditional Mueller matrix(MM)imaging technique based on single exposure has a limited dynamic range,leading to poor polarization image quality for biological samples with signi-cant contrast variations.In this study,we propose a novel method to generate high dynamic range(HDR)MM images based on a multi-exposure fusion algorithm.By employing an optimal exposure selection strategy for transmission imaging and a multi-exposure weighted averaging strategy for backscattering imaging,the method expands the dynamic range while accurately preserving the polarization information of the samples.Experiments of sliced and bulk tissues demonstrate that the proposed method signi¯cantly suppresses the scattering noise and improves the quality of extracted polarization parameter images,especially in accurate distinction of di®erent pathological areas.These results highlight the potential of HDR MM imaging technology in extracting polarization information from complex biological samples with high resolution and contrast.
基金funded by Natural Science Foundation of Jilin Province(20220101125JC)the National Natural Science Foundation of China(12273079).
文摘Lunar Laser Ranging has extremely high requirements for the pointing accuracy of the telescopes used.To improve its pointing accuracy and solve the problem of insufficiently accurate telescope pointing correction achieved by tracking stars in the all-sky region,we propose a processing scheme to select larger-sized lunar craters near the Lunar Corner Cube Retroreflector as reference features for telescope pointing bias computation.Accurately determining the position of the craters in the images is crucial for calculating the pointing bias;therefore,we propose a method for accurately calculating the crater position based on lunar surface feature matching.This method uses matched feature points obtained from image feature matching,using a deep learning method to solve the image transformation matrix.The known position of a crater in a reference image is mapped using this matrix to calculate the crater position in the target image.We validate this method using craters near the Lunar Corner Cube Retroreflectors of Apollo 15 and Luna 17 and find that the calculated position of a crater on the target image falls on the center of the crater,even for image features with large distortion near the lunar limb.The maximum image matching error is approximately 1″,and the minimum is only 0.47″,which meets the pointing requirements of Lunar Laser Ranging.This method provides a new technical means for the high-precision pointing bias calculation of the Lunar Laser Ranging system.
基金supported by the National Science Fund for Distinguished Young (61025006)the National Science Foundation for Young Scientists of China (61101182)
文摘Aiming at the reference range selection for different antennas in interferometric inverse synthetic aperture radar （InlSAR） systems, this paper proposes a respective focusing （RF） method. The reference ranges for echoes of different antennas are selected respectively for RF, which is different from the traditional uniform focusing （UF） with the same reference range applied to all the antennas. First, a comparison between UF and RF for InlSAR signal model considering the ranging error is given. Compared with RF, UF has an advantage in overcoming the ranging error differences between different antennas. Then the influence of ranging error upon the interferometric imaging with RF is investigated particularly, and it is found that the ranging error differences between different antennas are far smaller than the wavelength, which is advantageous to imaging. By comparing the capabilities of inter- ferometric imaging between RF and UF, it is concluded that RF is a better choice in conquering problems such as image mismatching and phase ambiguity even with ranging errors. Simulations demonstrate the validity of the proposed method.
基金Project supported by the Young Scientist Fund of the National Natural Science Foundation of China(Grant No.61108072)
文摘The range accuracy of three-dimensional（3D） ghost imaging is derived. Based on the derived range accuracy equation, the relationship between the slicing number and the range accuracy is analyzed and an optimum slicing number（OSN）is determined. According to the OSN, an improved 3D ghost imaging algorithm is proposed to increase the range accuracy. Experimental results indicate that the slicing number can affect the range accuracy significantly and the highest range accuracy can be achieved if the 3D ghost imaging system works with OSN.
文摘The ultraviolet (UV) photoresponses of Wurtzite GaN, ZnO, and 6H-SiC-based Optical Field Effect Transistor (OPFET) detectors are estimated with an in-depth analysis of the same considering the generalized model and the front-illuminated model for high resolution imaging and UV communication applications. The gate materials considered for the proposed study are gold (Au) and Indium-Tin-Oxide (ITO) for GaN, Au for SiC, and Au and silver dioxide (AgO2) for ZnO. The results indicate significant improvement in the Linear Dynamic Range (LDR) over the previously investigated GaN OPFET (buried-gate, front-illuminated and generalized) models with Au gate. The generalized model has superior dynamic range than the front-illuminated model. In terms of responsivity, all the models including buried-gate OPFET exhibit high and comparable photoresponses. Buried-gate devices on the whole, exhibit faster response than the surface gate models except in the AgO2-ZnO generalized OPFET model wherein the switching time is the lowest. The generalized model enables faster switching than the front-illuminated model. The switching times in all the cases are of the order of nanoseconds to picoseconds. The SiC generalized OPFET model shows the highest 3-dB bandwidths of 11.88 GHz, 36.2 GHz, and 364 GHz, and modest unity-gain cut-off frequencies of 4.62 GHz, 8.71 GHz, and 5.71 GHz at the optical power densities of 0.575 μW/cm2, 0.575 mW/cm2, and 0.575 W/cm2 respectively. These are in overall, the highest detection-cum-amplifi-cation bandwidths among all the investigated devices. The same device exhibits the highest LDR of 73.3 dB. The device performance is superior to most of the other existing detectors along with comparable LDR, thus, emerging as a high performance photodetector for imaging and communication applications. All the detectors show considerably high detectivities owing to the high responsivity values. The results have been analyzed by the photovoltaic and the photoconductive effects, and the series resistance effects and will aid in conducting further research. The results are in line with the experiments and the commercially available software simulations. The devices will greatly contribute towards single photon counting, high resolution imaging, and UV communication applications.
基金National Natural Science Foundation of China(No.62293493)。
文摘Three dimensional(3-D)imaging algorithms with irregular planar multiple-input-multiple-output(MIMO)arrays are discussed and compared with each other.Based on the same MIMO array,a modified back projection algorithm(MBPA)is accordingly proposed and four imaging algorithms are used for comparison,back-projection method(BP),back-projection one in time domain(BP-TD),modified back-projection one and fast Fourier transform(FFT)-based MIMO range migration algorithm(FFT-based MIMO RMA).All of the algorithms have been implemented in practical application scenarios by use of the proposed imaging system.Back to the practical applications,MIMO array-based imaging system with wide-bandwidth properties provides an efficient tool to detect objects hidden behind a wall.An MIMO imaging radar system,composed of a vector network analyzer(VNA),a set of switches,and an array of Vivaldi antennas,have been designed,fabricated,and tested.Then,these algorithms have been applied to measured data collected in different scenarios constituted by five metallic spheres in the absence and in the presence of a wall between the antennas and the targets in simulation and pliers in free space for experimental test.Finally,the focusing properties and time consumption of the above algorithms are compared.
