Due to improper acquisition settings and other noise artifacts,the image degraded to yield poor mean preservation in brightness.The simplest way to improve the preservation is the implementation of histogram equalizat...Due to improper acquisition settings and other noise artifacts,the image degraded to yield poor mean preservation in brightness.The simplest way to improve the preservation is the implementation of histogram equalization.Because of over-enhancement,it failed to preserve the mean brightness and produce the poor quality of the image.This paper proposes a multi-scale decomposi-tion for brightness preservation using gamma correction.After transformation to hue,saturation and intensity(HSI)channel,the 2D-discrete wavelet transform decomposed the intensity component into low and high-pass coefficients.At the next phase,gamma correction is used by auto-tuning the scale value.The scale is the modified constant value used in the logarithmic function.Further,the scale value is optimized to obtain better visual quality in the image.The optimized value is the weighted distribution of standard deviation-mean of low pass coefficients.Finally,the experimental result is estimated in terms of quality assessment measures used as absolute mean brightness error,the measure of information detail,signal to noise ratio and patch-based contrast quality in the image.By comparison,the proposed method proved to be suitably remarkable in retaining the mean brightness and better visual quality of the image.展开更多
Image enhancement utilizes intensity transformation functions to maximize the information content of enhanced images.This paper approaches the topic as an optimization problem and uses the bald eagle search(BES)algori...Image enhancement utilizes intensity transformation functions to maximize the information content of enhanced images.This paper approaches the topic as an optimization problem and uses the bald eagle search(BES)algorithm to achieve optimal results.In our proposed model,gamma correction and Retinex address color cast issues and enhance image edges and details.The final enhanced image is obtained through color balancing.The BES algorithm seeks the optimal solution through the selection,search,and swooping stages.However,it is prone to getting stuck in local optima and converges slowly.To overcome these limitations,we propose an improved BES algorithm(ABES)with enhanced population learning,position updates,and control parameters.ABES is employed to optimize the core parameters of gamma correction and Retinex to improve image quality,and the maximization of information entropy is utilized as the objective function.Real benchmark images are collected to validate its performance.Experimental results demonstrate that ABES outperforms the existing image enhancement methods,including the flower pollination algorithm,the chimp optimization algorithm,particle swarm optimization,and BES,in terms of information entropy,peak signal-to-noise ratio(PSNR),structural similarity index(SSIM),and patch-based contrast quality index(PCQI).ABES demonstrates superior performance both qualitatively and quantitatively,and it helps enhance prominent features and contrast in the images while maintaining the natural appearance of the original images.展开更多
In the past,sketches were a standard technique used for recognizing offenders and have remained a valuable tool for law enforcement and social security purposes.However,relying on eyewitness observations can lead to d...In the past,sketches were a standard technique used for recognizing offenders and have remained a valuable tool for law enforcement and social security purposes.However,relying on eyewitness observations can lead to discrepancies in the depictions of the sketch,depending on the experience and skills of the sketch artist.With the emergence of modern technologies such as Generative Adversarial Networks(GANs),generating images using verbal and textual cues is now possible,resulting in more accurate sketch depictions.In this study,we propose an adversarial network that generates human facial sketches using such cues provided by an observer.Additionally,we have introduced an Inverse Gamma Correction Technique to improve the training and enhance the quality of the generated sketches.To evaluate the effectiveness of our proposed method,we conducted experiments and analyzed the results using the inception score and Frechet Inception Distance metrics.Our proposed method achieved an overall inception score of 1.438±0.049 and a Frechet Inception Distance of 65.29,outperforming other state-of-the-art techniques.展开更多
Visible and infrared image fusion(VIF)aims to combine information from visible and infrared images into a single fused image.Previous VIF methods usually employ a color space transformation to keep the hue and saturat...Visible and infrared image fusion(VIF)aims to combine information from visible and infrared images into a single fused image.Previous VIF methods usually employ a color space transformation to keep the hue and saturation from the original visible image.However,for fast VIF methods,this operation accounts for the majority of the calculation and is the bottleneck preventing faster processing.In this paper,we propose a fast fusion method,FCDFusion,with little color deviation.It preserves color information without color space transformations,by directly operating in RGB color space.It incorporates gamma correction at little extra cost,allowing color and contrast to be rapidly improved.We regard the fusion process as a scaling operation on 3D color vectors,greatly simplifying the calculations.A theoretical analysis and experiments show that our method can achieve satisfactory results in only 7 FLOPs per pixel.Compared to state-of-theart fast,color-preserving methods using HSV color space,our method provides higher contrast at only half of the computational cost.We further propose a new metric,color deviation,to measure the ability of a VIF method to preserve color.It is specifically designed for VIF tasks with color visible-light images,and overcomes deficiencies of existing VIF metrics used for this purpose.Our code is available at https://github.com/HeasonLee/FCDFusion.展开更多
In some quantum gravity theories, a foamy structure of space-time may lead to Lorentz invariance violation（LIV）. As the most energetic explosions in the Universe, gamma-ray bursts（GRBs） provide an effect way to pr...In some quantum gravity theories, a foamy structure of space-time may lead to Lorentz invariance violation（LIV）. As the most energetic explosions in the Universe, gamma-ray bursts（GRBs） provide an effect way to probe quantum gravity effects. In this paper, we use the continuous spectra of 20 short GRBs detected by the Swift satellite to give a conservative lower limit of quantum gravity energy scale MQG. Due to the LIV effect, photons with different energy have different velocities. This will lead to the delayed arrival of high energy photons relative to low energy ones. Based on the fact that the LIV-induced time delay cannot be longer than the duration of a GRB,we present the most conservative estimate of the quantum gravity energy scales from 20 short GRBs. The strictest constraint, M_（QG） 〉 5.05 × 10^（14） GeV in the linearly corrected case, is from GRB 140622 A. Our constraint on MQG,although not as tight as previous results, is the safest and most reliable so far.展开更多
We have set up a novel system for shaping the Gaussian laser beams into super-Gaussian beams.The digital micro-mirror device(DMD)is able to modulate the laser light spatially through binary-amplitude modulation mechan...We have set up a novel system for shaping the Gaussian laser beams into super-Gaussian beams.The digital micro-mirror device(DMD)is able to modulate the laser light spatially through binary-amplitude modulation mechanism.With DMD,the irradiance of the laser beam can be redistributed flexibly and various beams with different intensity distribution can be produced.A super-Gaussian beam has been successfully shaped from the Gaussian beam with the use of DMD.This technique will be widely applied in lithography,quantum emulation and holographic optical tweezers which require precise control of beam profile.展开更多
文摘Due to improper acquisition settings and other noise artifacts,the image degraded to yield poor mean preservation in brightness.The simplest way to improve the preservation is the implementation of histogram equalization.Because of over-enhancement,it failed to preserve the mean brightness and produce the poor quality of the image.This paper proposes a multi-scale decomposi-tion for brightness preservation using gamma correction.After transformation to hue,saturation and intensity(HSI)channel,the 2D-discrete wavelet transform decomposed the intensity component into low and high-pass coefficients.At the next phase,gamma correction is used by auto-tuning the scale value.The scale is the modified constant value used in the logarithmic function.Further,the scale value is optimized to obtain better visual quality in the image.The optimized value is the weighted distribution of standard deviation-mean of low pass coefficients.Finally,the experimental result is estimated in terms of quality assessment measures used as absolute mean brightness error,the measure of information detail,signal to noise ratio and patch-based contrast quality in the image.By comparison,the proposed method proved to be suitably remarkable in retaining the mean brightness and better visual quality of the image.
基金supported by the Research on theKey Technology of Damage Identification Method of Dam Concrete Structure based on Transformer Image Processing(242102521031)the project Research on Situational Awareness and Behavior Anomaly Prediction of Social Media Based on Multimodal Time Series Graph(232102520004)Key Scientific Research Project of Higher Education Institutions in Henan Province(25B520019).
文摘Image enhancement utilizes intensity transformation functions to maximize the information content of enhanced images.This paper approaches the topic as an optimization problem and uses the bald eagle search(BES)algorithm to achieve optimal results.In our proposed model,gamma correction and Retinex address color cast issues and enhance image edges and details.The final enhanced image is obtained through color balancing.The BES algorithm seeks the optimal solution through the selection,search,and swooping stages.However,it is prone to getting stuck in local optima and converges slowly.To overcome these limitations,we propose an improved BES algorithm(ABES)with enhanced population learning,position updates,and control parameters.ABES is employed to optimize the core parameters of gamma correction and Retinex to improve image quality,and the maximization of information entropy is utilized as the objective function.Real benchmark images are collected to validate its performance.Experimental results demonstrate that ABES outperforms the existing image enhancement methods,including the flower pollination algorithm,the chimp optimization algorithm,particle swarm optimization,and BES,in terms of information entropy,peak signal-to-noise ratio(PSNR),structural similarity index(SSIM),and patch-based contrast quality index(PCQI).ABES demonstrates superior performance both qualitatively and quantitatively,and it helps enhance prominent features and contrast in the images while maintaining the natural appearance of the original images.
文摘In the past,sketches were a standard technique used for recognizing offenders and have remained a valuable tool for law enforcement and social security purposes.However,relying on eyewitness observations can lead to discrepancies in the depictions of the sketch,depending on the experience and skills of the sketch artist.With the emergence of modern technologies such as Generative Adversarial Networks(GANs),generating images using verbal and textual cues is now possible,resulting in more accurate sketch depictions.In this study,we propose an adversarial network that generates human facial sketches using such cues provided by an observer.Additionally,we have introduced an Inverse Gamma Correction Technique to improve the training and enhance the quality of the generated sketches.To evaluate the effectiveness of our proposed method,we conducted experiments and analyzed the results using the inception score and Frechet Inception Distance metrics.Our proposed method achieved an overall inception score of 1.438±0.049 and a Frechet Inception Distance of 65.29,outperforming other state-of-the-art techniques.
基金supported by the National Natural Science Foundation of China under Grant Nos.62171038,61827901,and 62088101.
文摘Visible and infrared image fusion(VIF)aims to combine information from visible and infrared images into a single fused image.Previous VIF methods usually employ a color space transformation to keep the hue and saturation from the original visible image.However,for fast VIF methods,this operation accounts for the majority of the calculation and is the bottleneck preventing faster processing.In this paper,we propose a fast fusion method,FCDFusion,with little color deviation.It preserves color information without color space transformations,by directly operating in RGB color space.It incorporates gamma correction at little extra cost,allowing color and contrast to be rapidly improved.We regard the fusion process as a scaling operation on 3D color vectors,greatly simplifying the calculations.A theoretical analysis and experiments show that our method can achieve satisfactory results in only 7 FLOPs per pixel.Compared to state-of-theart fast,color-preserving methods using HSV color space,our method provides higher contrast at only half of the computational cost.We further propose a new metric,color deviation,to measure the ability of a VIF method to preserve color.It is specifically designed for VIF tasks with color visible-light images,and overcomes deficiencies of existing VIF metrics used for this purpose.Our code is available at https://github.com/HeasonLee/FCDFusion.
基金Supported by National Natural Science Foundation of China(11375203,11305181,11322545,11335012)Knowledge Innovation Program of The Chinese Academy of Sciences
文摘In some quantum gravity theories, a foamy structure of space-time may lead to Lorentz invariance violation（LIV）. As the most energetic explosions in the Universe, gamma-ray bursts（GRBs） provide an effect way to probe quantum gravity effects. In this paper, we use the continuous spectra of 20 short GRBs detected by the Swift satellite to give a conservative lower limit of quantum gravity energy scale MQG. Due to the LIV effect, photons with different energy have different velocities. This will lead to the delayed arrival of high energy photons relative to low energy ones. Based on the fact that the LIV-induced time delay cannot be longer than the duration of a GRB,we present the most conservative estimate of the quantum gravity energy scales from 20 short GRBs. The strictest constraint, M_（QG） 〉 5.05 × 10^（14） GeV in the linearly corrected case, is from GRB 140622 A. Our constraint on MQG,although not as tight as previous results, is the safest and most reliable so far.
基金supported by the National Natural Science Foundation of China(Grant No.60974038)the Project of Provincial Teaching Research in Anhui Institutions of Higher Education(Grant No.2012jyxm006)
文摘We have set up a novel system for shaping the Gaussian laser beams into super-Gaussian beams.The digital micro-mirror device(DMD)is able to modulate the laser light spatially through binary-amplitude modulation mechanism.With DMD,the irradiance of the laser beam can be redistributed flexibly and various beams with different intensity distribution can be produced.A super-Gaussian beam has been successfully shaped from the Gaussian beam with the use of DMD.This technique will be widely applied in lithography,quantum emulation and holographic optical tweezers which require precise control of beam profile.
