Underwater images are inherently degraded by color distortion,contrast reduction,and uneven brightness,primarily due to light absorption and scattering in water.To mitigate these challenges,a novel enhancement approac...Underwater images are inherently degraded by color distortion,contrast reduction,and uneven brightness,primarily due to light absorption and scattering in water.To mitigate these challenges,a novel enhancement approach is proposed,integrating Local Adaptive Color Correction(LACC)with contrast enhancement based on adaptive Rayleigh distribution stretching and CLAHE(LACC-RCE).Conventional color correction methods predominantly employ global adjustment strategies,which are often inadequate for handling spatially varying color distortions.In contrast,the proposed LACC method incorporates local color analysis,tone-weighted control,and spatially adaptive adjustments,allowing for region-specific color correction.This approach effectively enhances color fidelity and perceptual naturalness,addressing the limitations of global correction techniques.For contrast enhancement,the proposed method leverages the global mapping characteristics of the Rayleigh distribution to improve overall contrast,while CLAHE is employed to adaptively enhance local regions.A weighted fusion strategy is then applied to synthesize high-quality underwater images.Experimental results indicate that LACC-RCE surpasses conventional methods in color restoration,contrast optimization,and detail preservation,thereby enhancing the visual quality of underwater images.This improvement facilitates more reliable inputs for underwater object detection and recognition tasks.展开更多
Systems using numerous cameras are emerging in many fields due to their ease of production and reduced cost, and one of the fields where they are expected to be used more actively in the near future is in image-based ...Systems using numerous cameras are emerging in many fields due to their ease of production and reduced cost, and one of the fields where they are expected to be used more actively in the near future is in image-based rendering （IBR）. Color correction between views is necessary to use multi-view systems in IBR to make audiences feel comfortable when views are switched or when a free viewpoint video is displayed. Color correction usually involves two steps： the first is to adjust camera parameters such as gain, brightness, and aperture before capture, and the second is to modify captured videos through image processing. This paper deals with the latter, which does not need a color pattern board. The proposed method uses scale invariant feature transform （SIFT） to detect correspondences, treats RGB channels independently, calculates lookup tables with an energy-minimization approach, and corrects captured video with these tables. The experimental results reveal that this approach works well.展开更多
The subtle color distinction is the important function of electronic endoscope imaging diagnosis.However,after image acquisition,transmission and display,color distortions of intracorporeal organs or tissues occur ine...The subtle color distinction is the important function of electronic endoscope imaging diagnosis.However,after image acquisition,transmission and display,color distortions of intracorporeal organs or tissues occur inevitably,which are adverse to analyze image features accurately or to diagnose early pathological changes.A real-time color correction algorithm based on fourneighborhood and polynomial regression in YUV color space is proposed.Based on polynomial regression the color correction matrix is calculated in YUV color space according to the dierences between standard values of color checker and measured values of that imaged by the endoscope.As the correction is only executed on U and V components in YUV color space,the defect that the color of corrected images in RGB color space will change along with luminance can be avoided,and then the stability of image color is improved.Owing to four-neighborhood processing,the signal-to-noise ratio of corrected images is enhanced and the processing speed of correction algorithm is accelerated.The average color dierence is reduced from 0.3944 to 0.2850 by application of the proposed algorithm in high-denition electronic endoscope.A total of 17 frames per second can be achieved at the resolution of 1280800,and the color characteristics of the image after processing match that of human visual system.展开更多
Color inconsistency between views is an important problem to be solved in multi-view video systems. A multi-view video color correction method using dynamic programming is proposed. Three-dimensional histograms are co...Color inconsistency between views is an important problem to be solved in multi-view video systems. A multi-view video color correction method using dynamic programming is proposed. Three-dimensional histograms are constructed with sequential conditional probability in HSI color space. Then, dynamic programming is used to seek the best color mapping relation with the minimum cost path between target image histogram and source image histogram. Finally, video tracking technique is performed to correct multi-view video. Experimental results show that the proposed method can obtain better subjective and objective performance in color correction.展开更多
Color inconsistency between views is an important problem to be solved in multi-view video applications, such as free viewpoint television and other three-dimensional video systems. In this paper, by combining with mu...Color inconsistency between views is an important problem to be solved in multi-view video applications, such as free viewpoint television and other three-dimensional video systems. In this paper, by combining with multi-view video coding, a coding-oriented multi-view video color correction method is proposed. We first separate foreground and background in first Group Of Pictures （GOP） by using SKIP coding mode. Then by transferring means and standard deviations in backgrounds, color correction is performed for each frame in GOP, and multi-view video coding is performed and used to renew the backgrounds. Experimental results ances in color correction and multi-view video show the proposed method can obtain better performcoding.展开更多
trast （HC） method is proposed to define saliency value of each pixel, then auto Grabcut segmenta- tion method is used to segment the salient region so as to obtain a region of interest （ROI）. After that, normalize...trast （HC） method is proposed to define saliency value of each pixel, then auto Grabcut segmenta- tion method is used to segment the salient region so as to obtain a region of interest （ROI）. After that, normalized histograms and cumulative histograms for ROI and region of background （ROB） are calculated. The mapping functions of the corresponding regions are derived from reference image to distorted image through the nearest cumulative histogram matching method, so that color correction can be finally achieved. Experimental results show that benefitting from the separate treatment to ROI and ROB, the proposed color correction method could avoid error propagation between the two different regions, which achieves good color correction result in comparison with other correction methods.展开更多
Underwater images often exhibit severe color deviations and degraded visibility,which limits many practical applications in ocean engineering.Although extensive research has been conducted into underwater image enhanc...Underwater images often exhibit severe color deviations and degraded visibility,which limits many practical applications in ocean engineering.Although extensive research has been conducted into underwater image enhancement,little of which demonstrates the significant robustness and generalization for diverse real-world underwater scenes.In this paper,we propose an adaptive color correction algorithm based on the maximum likelihood estimation of Gaussian parameters,which effectively removes color casts of a variety of underwater images.A novel algorithm using weighted combination of gradient maps in HSV color space and absolute difference of intensity for accurate background light estimation is proposed,which circumvents the influence of white or bright regions that challenges existing physical model-based methods.To enhance contrast of resultant images,a piece-wise affine transform is applied to the transmission map estimated via background light differential.Finally,with the estimated background light and transmission map,the scene radiance is recovered by addressing an inverse problem of image formation model.Extensive experiments reveal that our results are characterized by natural appearance and genuine color,and our method achieves competitive performance with the state-of-the-art methods in terms of objective evaluation metrics,which further validates the better robustness and higher generalization ability of our enhancement model.展开更多
With the development of digital library technology, library books made of paper can be digital released and read, and Endangered Cultural Heritages can be preserved. Traditional library＇s contents and functions can b...With the development of digital library technology, library books made of paper can be digital released and read, and Endangered Cultural Heritages can be preserved. Traditional library＇s contents and functions can be greatly enhanced by digital technologies. For these new library objects, the primary key problem is precisely reconstructing their 3D models. When constructing complete 3D models, multiple color texture maps are often necessary. A commonly encountered problem uncounted during fusing of textures from multiple color images is color distortion. Each texture of a single 3D model may be obtained under possibly different lighting conditions and color response of the camera. To remove any visible seam and improve color consistency between the textures while avoiding color distortion, we propose a new efficient algorithm to relight all the texture images globally, spread residual light difference, and recolor each image by homogeneous transformation. A relative illumination model was adopted to obtain the relighting function. We choose lαβ color space with minimal correlation between channels for many natural scenes, for calculating the relighting result. Looking into two overlapped images A and B, we can pairwise relight B into A＇s luminosity condition in two steps. We first scale B＇s l channel by the lA/lB ratio of the overlapped region. We can assume A and B are in a same color plane now. Then a homogeneous transformation is applied to B＇s a and fl channels which moves B into A＇s hue and saturation condition. For multiple overlapped color textures, a patch based weighted global relighting method was proposed to minimize the total color difference. The pairwise relighting method was used between each two overlapped images, and the difference in every overlapped region after relighting was weighted and summed up to construct an energy value. We used Nelder-Mead method to find a minimal energy value and the relighting parameters for every image. After global relighting, textures become almost coherent. We simply blended the overlapped region along the texture border to remove small visual seams and get a final result. We illustrate our method by calibrating textures of a painted sculpture acquired with laser scanner. Experimental results were realistic and reliable and showed how this method can fuse multiple textures without color distortion.展开更多
To acquire high-quality operational data products for Chinese in-orbit and scheduled ocean color sensors, the performances of two operational atmospheric correction(AC) algorithms(ESA MEGS 7.4.1 and NASA Sea DAS 6.1) ...To acquire high-quality operational data products for Chinese in-orbit and scheduled ocean color sensors, the performances of two operational atmospheric correction(AC) algorithms(ESA MEGS 7.4.1 and NASA Sea DAS 6.1) were evaluated over the East China Seas(ECS) using MERIS data. The spectral remote sensing reflectance R_(rs)(λ), aerosol optical thickness(AOT), and ?ngstr?m exponent(α) retrieved using the two algorithms were validated using in situ measurements obtained between May 2002 and October 2009. Match-ups of R_(rs), AOT, and α between the in situ and MERIS data were obtained through strict exclusion criteria. Statistical analysis of R_(rs)(λ) showed a mean percentage difference(MPD) of 9%–13% in the 490–560 nm spectral range, and significant overestimation was observed at 413 nm(MPD>72%). The AOTs were overestimated(MPD>32%), and although the ESA algorithm outperformed the NASA algorithm in the blue-green bands, the situation was reversed in the red-near-infrared bands. The value of α was obviously underestimated by the ESA algorithm(MPD=41%) but not by the NASA algorithm(MPD=35%). To clarify why the NASA algorithm performed better in the retrieval of α, scatter plots of the α single scattering albedo(SSA) density were prepared. These α-SSA density scatter plots showed that the applicability of the aerosol models used by the NASA algorithm over the ECS is better than that used by the ESA algorithm, although neither aerosol model is suitable for the ECS region. The results of this study provide a reference to both data users and data agencies regarding the use of operational data products and the investigation into the improvement of current AC schemes over the ECS.展开更多
Low-light images suffer from low quality due to poor lighting conditions,noise pollution,and improper settings of cameras.To enhance low-light images,most existing methods rely on normal-light images for guidance but ...Low-light images suffer from low quality due to poor lighting conditions,noise pollution,and improper settings of cameras.To enhance low-light images,most existing methods rely on normal-light images for guidance but the collection of suitable normal-light images is difficult.In contrast,a self-supervised method breaks free from the reliance on normal-light data,resulting in more convenience and better generalization.Existing self-supervised methods primarily focus on illumination adjustment and design pixel-based adjustment methods,resulting in remnants of other degradations,uneven brightness and artifacts.In response,this paper proposes a self-supervised enhancement method,termed as SLIE.It can handle multiple degradations including illumination attenuation,noise pollution,and color shift,all in a self-supervised manner.Illumination attenuation is estimated based on physical principles and local neighborhood information.The removal and correction of noise and color shift removal are solely realized with noisy images and images with color shifts.Finally,the comprehensive and fully self-supervised approach can achieve better adaptability and generalization.It is applicable to various low light conditions,and can reproduce the original color of scenes in natural light.Extensive experiments conducted on four public datasets demonstrate the superiority of SLIE to thirteen state-of-the-art methods.Our code is available at https://github.com/hanna-xu/SLIE.展开更多
Improper functioning, or lack, of human cone cells leads to vision defects, making it impossible for affected persons to distinguish certain colors. Colorblind persons have color perception, but their ability to captu...Improper functioning, or lack, of human cone cells leads to vision defects, making it impossible for affected persons to distinguish certain colors. Colorblind persons have color perception, but their ability to capture color information differs from that of normal people: colorblind and normal people perceive the same image differently. It is necessary to devise solutions to help persons with color blindness understand images and distinguish different colors. Most research on this subject is aimed at adjusting insensitive colors,enabling colorblind persons to better capture color information, but ignores the attention paid by colorblind persons to the salient areas of images. The areas of the image seen as salient by normal people generally differ from those seen by the colorblind. To provide the same saliency for colorblind persons and normal people, we propose a saliency-based image correction algorithm for color blindness. Adjusted colors in the adjusted image are harmonious and realistic, and the method is practical. Our experimental results show that this method effectively improves images, enabling the colorblind to see the same salient areas as normal people.展开更多
The selective attenuation and scattering of light in underwater environments cause color distortion and contrast reduction in underwater images,which can impede the ever-growing demand for underwater robot operations....The selective attenuation and scattering of light in underwater environments cause color distortion and contrast reduction in underwater images,which can impede the ever-growing demand for underwater robot operations.To address these issues,we propose a Multi-Color space Residual Network(MCRNet)for underwater image enhancement.Our method takes advantage of the unique features of color representation in the RGB,HSV,and Lab color spaces.By utilizing the distinct feature representations of images in different color spaces,we can highlight and fuse the most informative features of the three color spaces.Our approach employs a self-attention mechanism in the multi-color space feature fusion module.Extensive experiments demonstrate that our method achieves satisfactory results in color correction and contrast improvement of underwater images,particularly in severely degraded scenes.Consequently,our method outperforms state-of-the-art methods in both subjective visual comparison and objective evaluation metrics.展开更多
Multiview video can provide more immersive perception than traditional single 2-D video. It enables both interactive free navigation applications as well as high-end autostereoscopic displays on which multiple users c...Multiview video can provide more immersive perception than traditional single 2-D video. It enables both interactive free navigation applications as well as high-end autostereoscopic displays on which multiple users can perceive genuine 3-D content without glasses. The multiview format also comprises much more visual information than classical 2-D or stereo 3-D content, which makes it possible to perform various interesting editing operations both on pixel-level and object-level. This survey provides a comprehensive review of existing multiview video synthesis and editing algorithms and applications. For each topic, the related technologies in classical 2-D image and video processing are reviewed. We then continue to the discussion of recent advanced techniques for multiview video virtual view synthesis and various interactive editing applications. Due to the ongoing progress on multiview video synthesis and editing, we can foresee more and more immersive 3-D video applications will appear in the future.展开更多
基金Graduate Student Innovation Projects of Beijing University of Civil Engineering and Architecture(No.PG2024121)。
文摘Underwater images are inherently degraded by color distortion,contrast reduction,and uneven brightness,primarily due to light absorption and scattering in water.To mitigate these challenges,a novel enhancement approach is proposed,integrating Local Adaptive Color Correction(LACC)with contrast enhancement based on adaptive Rayleigh distribution stretching and CLAHE(LACC-RCE).Conventional color correction methods predominantly employ global adjustment strategies,which are often inadequate for handling spatially varying color distortions.In contrast,the proposed LACC method incorporates local color analysis,tone-weighted control,and spatially adaptive adjustments,allowing for region-specific color correction.This approach effectively enhances color fidelity and perceptual naturalness,addressing the limitations of global correction techniques.For contrast enhancement,the proposed method leverages the global mapping characteristics of the Rayleigh distribution to improve overall contrast,while CLAHE is employed to adaptively enhance local regions.A weighted fusion strategy is then applied to synthesize high-quality underwater images.Experimental results indicate that LACC-RCE surpasses conventional methods in color restoration,contrast optimization,and detail preservation,thereby enhancing the visual quality of underwater images.This improvement facilitates more reliable inputs for underwater object detection and recognition tasks.
文摘Systems using numerous cameras are emerging in many fields due to their ease of production and reduced cost, and one of the fields where they are expected to be used more actively in the near future is in image-based rendering （IBR）. Color correction between views is necessary to use multi-view systems in IBR to make audiences feel comfortable when views are switched or when a free viewpoint video is displayed. Color correction usually involves two steps： the first is to adjust camera parameters such as gain, brightness, and aperture before capture, and the second is to modify captured videos through image processing. This paper deals with the latter, which does not need a color pattern board. The proposed method uses scale invariant feature transform （SIFT） to detect correspondences, treats RGB channels independently, calculates lookup tables with an energy-minimization approach, and corrects captured video with these tables. The experimental results reveal that this approach works well.
基金supported by grants from National Key Technology R&D Program(Grant No.:2011BAI12B06)the Fundamental Research Funds for the Central Universities(Grant No.:2012FZA5023).
文摘The subtle color distinction is the important function of electronic endoscope imaging diagnosis.However,after image acquisition,transmission and display,color distortions of intracorporeal organs or tissues occur inevitably,which are adverse to analyze image features accurately or to diagnose early pathological changes.A real-time color correction algorithm based on fourneighborhood and polynomial regression in YUV color space is proposed.Based on polynomial regression the color correction matrix is calculated in YUV color space according to the dierences between standard values of color checker and measured values of that imaged by the endoscope.As the correction is only executed on U and V components in YUV color space,the defect that the color of corrected images in RGB color space will change along with luminance can be avoided,and then the stability of image color is improved.Owing to four-neighborhood processing,the signal-to-noise ratio of corrected images is enhanced and the processing speed of correction algorithm is accelerated.The average color dierence is reduced from 0.3944 to 0.2850 by application of the proposed algorithm in high-denition electronic endoscope.A total of 17 frames per second can be achieved at the resolution of 1280800,and the color characteristics of the image after processing match that of human visual system.
基金supported by the National Natural Science Foundation of China (60672073)the Program for New Century Excellent Talents in University (NCET-06-0537)+1 种基金the Natural Science Foundation of Ningbo (2008A610016)the K.C.Wong Magna Fund in Ningbo University.
文摘Color inconsistency between views is an important problem to be solved in multi-view video systems. A multi-view video color correction method using dynamic programming is proposed. Three-dimensional histograms are constructed with sequential conditional probability in HSI color space. Then, dynamic programming is used to seek the best color mapping relation with the minimum cost path between target image histogram and source image histogram. Finally, video tracking technique is performed to correct multi-view video. Experimental results show that the proposed method can obtain better subjective and objective performance in color correction.
基金the National Natural Science Foundation of China (No.60672073, No.60872094)the Program for New Century Excellent Talents in University (NCET-06-0537)+2 种基金the Key Project of Chinese Ministry of Education (No. 206059)Scientific Research Fund of Zhejiang Provincial Education Department (No.20070962)the Natural Science Foundation of Ningbo (No.2008A610016).
文摘Color inconsistency between views is an important problem to be solved in multi-view video applications, such as free viewpoint television and other three-dimensional video systems. In this paper, by combining with multi-view video coding, a coding-oriented multi-view video color correction method is proposed. We first separate foreground and background in first Group Of Pictures （GOP） by using SKIP coding mode. Then by transferring means and standard deviations in backgrounds, color correction is performed for each frame in GOP, and multi-view video coding is performed and used to renew the backgrounds. Experimental results ances in color correction and multi-view video show the proposed method can obtain better performcoding.
基金Supported by the Natural Science Foundation of China(No.61311140262,61171163,61271021)
文摘trast （HC） method is proposed to define saliency value of each pixel, then auto Grabcut segmenta- tion method is used to segment the salient region so as to obtain a region of interest （ROI）. After that, normalized histograms and cumulative histograms for ROI and region of background （ROB） are calculated. The mapping functions of the corresponding regions are derived from reference image to distorted image through the nearest cumulative histogram matching method, so that color correction can be finally achieved. Experimental results show that benefitting from the separate treatment to ROI and ROB, the proposed color correction method could avoid error propagation between the two different regions, which achieves good color correction result in comparison with other correction methods.
基金supported by Higher Education Scientific Research Project of Ningxia(NGY2017009).
文摘Underwater images often exhibit severe color deviations and degraded visibility,which limits many practical applications in ocean engineering.Although extensive research has been conducted into underwater image enhancement,little of which demonstrates the significant robustness and generalization for diverse real-world underwater scenes.In this paper,we propose an adaptive color correction algorithm based on the maximum likelihood estimation of Gaussian parameters,which effectively removes color casts of a variety of underwater images.A novel algorithm using weighted combination of gradient maps in HSV color space and absolute difference of intensity for accurate background light estimation is proposed,which circumvents the influence of white or bright regions that challenges existing physical model-based methods.To enhance contrast of resultant images,a piece-wise affine transform is applied to the transmission map estimated via background light differential.Finally,with the estimated background light and transmission map,the scene radiance is recovered by addressing an inverse problem of image formation model.Extensive experiments reveal that our results are characterized by natural appearance and genuine color,and our method achieves competitive performance with the state-of-the-art methods in terms of objective evaluation metrics,which further validates the better robustness and higher generalization ability of our enhancement model.
基金Project supported by the National Basic Research Program (973) ofChina (No. 2002CB312106)
文摘With the development of digital library technology, library books made of paper can be digital released and read, and Endangered Cultural Heritages can be preserved. Traditional library＇s contents and functions can be greatly enhanced by digital technologies. For these new library objects, the primary key problem is precisely reconstructing their 3D models. When constructing complete 3D models, multiple color texture maps are often necessary. A commonly encountered problem uncounted during fusing of textures from multiple color images is color distortion. Each texture of a single 3D model may be obtained under possibly different lighting conditions and color response of the camera. To remove any visible seam and improve color consistency between the textures while avoiding color distortion, we propose a new efficient algorithm to relight all the texture images globally, spread residual light difference, and recolor each image by homogeneous transformation. A relative illumination model was adopted to obtain the relighting function. We choose lαβ color space with minimal correlation between channels for many natural scenes, for calculating the relighting result. Looking into two overlapped images A and B, we can pairwise relight B into A＇s luminosity condition in two steps. We first scale B＇s l channel by the lA/lB ratio of the overlapped region. We can assume A and B are in a same color plane now. Then a homogeneous transformation is applied to B＇s a and fl channels which moves B into A＇s hue and saturation condition. For multiple overlapped color textures, a patch based weighted global relighting method was proposed to minimize the total color difference. The pairwise relighting method was used between each two overlapped images, and the difference in every overlapped region after relighting was weighted and summed up to construct an energy value. We used Nelder-Mead method to find a minimal energy value and the relighting parameters for every image. After global relighting, textures become almost coherent. We simply blended the overlapped region along the texture border to remove small visual seams and get a final result. We illustrate our method by calibrating textures of a painted sculpture acquired with laser scanner. Experimental results were realistic and reliable and showed how this method can fuse multiple textures without color distortion.
基金Supported by the State Key Program of National Natural Science Foundation of China(No.60638020)the State Scholarship Fund of the China Scholarship Council(CSC)+1 种基金the National Natural Science Foundation of China(Nos.41321004,41276028,41206006,41306192,41306035)the Natural Science Foundation of Zhejiang Province(No.LY15D060001)
文摘To acquire high-quality operational data products for Chinese in-orbit and scheduled ocean color sensors, the performances of two operational atmospheric correction(AC) algorithms(ESA MEGS 7.4.1 and NASA Sea DAS 6.1) were evaluated over the East China Seas(ECS) using MERIS data. The spectral remote sensing reflectance R_(rs)(λ), aerosol optical thickness(AOT), and ?ngstr?m exponent(α) retrieved using the two algorithms were validated using in situ measurements obtained between May 2002 and October 2009. Match-ups of R_(rs), AOT, and α between the in situ and MERIS data were obtained through strict exclusion criteria. Statistical analysis of R_(rs)(λ) showed a mean percentage difference(MPD) of 9%–13% in the 490–560 nm spectral range, and significant overestimation was observed at 413 nm(MPD>72%). The AOTs were overestimated(MPD>32%), and although the ESA algorithm outperformed the NASA algorithm in the blue-green bands, the situation was reversed in the red-near-infrared bands. The value of α was obviously underestimated by the ESA algorithm(MPD=41%) but not by the NASA algorithm(MPD=35%). To clarify why the NASA algorithm performed better in the retrieval of α, scatter plots of the α single scattering albedo(SSA) density were prepared. These α-SSA density scatter plots showed that the applicability of the aerosol models used by the NASA algorithm over the ECS is better than that used by the ESA algorithm, although neither aerosol model is suitable for the ECS region. The results of this study provide a reference to both data users and data agencies regarding the use of operational data products and the investigation into the improvement of current AC schemes over the ECS.
基金supported by the National Natural Science Foundation of China(62276192)。
文摘Low-light images suffer from low quality due to poor lighting conditions,noise pollution,and improper settings of cameras.To enhance low-light images,most existing methods rely on normal-light images for guidance but the collection of suitable normal-light images is difficult.In contrast,a self-supervised method breaks free from the reliance on normal-light data,resulting in more convenience and better generalization.Existing self-supervised methods primarily focus on illumination adjustment and design pixel-based adjustment methods,resulting in remnants of other degradations,uneven brightness and artifacts.In response,this paper proposes a self-supervised enhancement method,termed as SLIE.It can handle multiple degradations including illumination attenuation,noise pollution,and color shift,all in a self-supervised manner.Illumination attenuation is estimated based on physical principles and local neighborhood information.The removal and correction of noise and color shift removal are solely realized with noisy images and images with color shifts.Finally,the comprehensive and fully self-supervised approach can achieve better adaptability and generalization.It is applicable to various low light conditions,and can reproduce the original color of scenes in natural light.Extensive experiments conducted on four public datasets demonstrate the superiority of SLIE to thirteen state-of-the-art methods.Our code is available at https://github.com/hanna-xu/SLIE.
基金the National Natural Science Foundation of China(Grant Nos.61772319,61976125,61873177,and 61773244)Shandong Natural Science Foundation of China(Grant No.ZR2017MF049)。
文摘Improper functioning, or lack, of human cone cells leads to vision defects, making it impossible for affected persons to distinguish certain colors. Colorblind persons have color perception, but their ability to capture color information differs from that of normal people: colorblind and normal people perceive the same image differently. It is necessary to devise solutions to help persons with color blindness understand images and distinguish different colors. Most research on this subject is aimed at adjusting insensitive colors,enabling colorblind persons to better capture color information, but ignores the attention paid by colorblind persons to the salient areas of images. The areas of the image seen as salient by normal people generally differ from those seen by the colorblind. To provide the same saliency for colorblind persons and normal people, we propose a saliency-based image correction algorithm for color blindness. Adjusted colors in the adjusted image are harmonious and realistic, and the method is practical. Our experimental results show that this method effectively improves images, enabling the colorblind to see the same salient areas as normal people.
基金supported in part by the National Key R&D Program of China(2022YFB4702300)in part by the National Natural Science Foundation of China(62273097)+3 种基金in part by the Guangdong Basic and Applied Basic Research Foundation,China(2022A1515140044,2019A1515110304,2020A1515110255,and 2021B1515120017)in part by the Research Foundation of Universities of Guangdong Province,China(2019KZDZX1026,2020KCXTD015,and 2021KCXTD083)in part by the Foshan Key Area Technology Research Foundation,China(2120001011009)in part by the Guangdong Philosophy and Social Science Program,China(GD23XTS03).
文摘The selective attenuation and scattering of light in underwater environments cause color distortion and contrast reduction in underwater images,which can impede the ever-growing demand for underwater robot operations.To address these issues,we propose a Multi-Color space Residual Network(MCRNet)for underwater image enhancement.Our method takes advantage of the unique features of color representation in the RGB,HSV,and Lab color spaces.By utilizing the distinct feature representations of images in different color spaces,we can highlight and fuse the most informative features of the three color spaces.Our approach employs a self-attention mechanism in the multi-color space feature fusion module.Extensive experiments demonstrate that our method achieves satisfactory results in color correction and contrast improvement of underwater images,particularly in severely degraded scenes.Consequently,our method outperforms state-of-the-art methods in both subjective visual comparison and objective evaluation metrics.
基金partially supported by Innoviris(3-DLicornea project)FWO(project G.0256.15)+3 种基金supported by the National Natural Science Foundation of China(Nos.61272226 and 61373069)Research Grant of Beijing Higher Institution Engineering Research CenterTsinghua-Tencent Joint Laboratory for Internet Innovation TechnologyTsinghua University Initiative Scientific Research Program
文摘Multiview video can provide more immersive perception than traditional single 2-D video. It enables both interactive free navigation applications as well as high-end autostereoscopic displays on which multiple users can perceive genuine 3-D content without glasses. The multiview format also comprises much more visual information than classical 2-D or stereo 3-D content, which makes it possible to perform various interesting editing operations both on pixel-level and object-level. This survey provides a comprehensive review of existing multiview video synthesis and editing algorithms and applications. For each topic, the related technologies in classical 2-D image and video processing are reviewed. We then continue to the discussion of recent advanced techniques for multiview video virtual view synthesis and various interactive editing applications. Due to the ongoing progress on multiview video synthesis and editing, we can foresee more and more immersive 3-D video applications will appear in the future.
