Objective evaluations of fused images are important in comparing the performance of different image fusion algorithms. This paper describes a structural similarity metric that does not use a reference image for image ...Objective evaluations of fused images are important in comparing the performance of different image fusion algorithms. This paper describes a structural similarity metric that does not use a reference image for image fusion evaluations. The metric is based on the universal image quality index and addresses not only the similarities between the input images and the fused image, but also the similarities among the input images. The evaluation process distinguishes between complementary information and redundant information using similarities among the input images. The metric uses the information classification to estimate how much structural similarity is preserved in the fused image. Tests demonstrate that the metric correlates well with subjective evaluations of the fused images.展开更多
Omni-directional imaging system is becoming more and more common in reducing the maintenance fees and the number of cameras used as well as increasing the angle of view in a single camera. Due to omni-directional imag...Omni-directional imaging system is becoming more and more common in reducing the maintenance fees and the number of cameras used as well as increasing the angle of view in a single camera. Due to omni-directional images are not directly understandable, an approach namely the un-warping process, has been implemented in converting the omni-directional image to a panoramic image, making it understandable. There are different kinds of methods used for the implementation of this approach. This paper evaluates the performance of the 3 universal un-warping methods currently applied actively around the world in transforming omni-directional image to panoramic image, namely the pano-mapping table method, discrete geometry method （DGT） and the log-polar mapping method. The algorithm of these methods will first be proposed, and the code will then be generated and be tested on several different omni-directional images. The images converted will then be compared among each other and be evaluated based on their performance on the resolutions, quality, algorithm used, complexity based on Big-O computations, processing time, and finally their data compression rate available for each of the methods. The most preferable un-warping method will then be concluded, taking into considerations all these factors.展开更多
In many applications of computer graphics,art,and design,it is desirable for a user to provide intuitive non-image input,such as text,sketch,stroke,graph,or layout,and have a computer system automatically generate pho...In many applications of computer graphics,art,and design,it is desirable for a user to provide intuitive non-image input,such as text,sketch,stroke,graph,or layout,and have a computer system automatically generate photo-realistic images according to that input.While classically,works that allow such automatic image content generation have followed a framework of image retrieval and composition,recent advances in deep generative models such as generative adversarial networks(GANs),variational autoencoders(VAEs),and flow-based methods have enabled more powerful and versatile image generation approaches.This paper reviews recent works for image synthesis given intuitive user input,covering advances in input versatility,image generation methodology,benchmark datasets,and evaluation metrics.This motivates new perspectives on input representation and interactivity,cross fertilization between major image generation paradigms,and evaluation and comparison of generation methods.展开更多
基金Supported by the National Natural Science Foundation of China (No.60673024)
文摘Objective evaluations of fused images are important in comparing the performance of different image fusion algorithms. This paper describes a structural similarity metric that does not use a reference image for image fusion evaluations. The metric is based on the universal image quality index and addresses not only the similarities between the input images and the fused image, but also the similarities among the input images. The evaluation process distinguishes between complementary information and redundant information using similarities among the input images. The metric uses the information classification to estimate how much structural similarity is preserved in the fused image. Tests demonstrate that the metric correlates well with subjective evaluations of the fused images.
文摘Omni-directional imaging system is becoming more and more common in reducing the maintenance fees and the number of cameras used as well as increasing the angle of view in a single camera. Due to omni-directional images are not directly understandable, an approach namely the un-warping process, has been implemented in converting the omni-directional image to a panoramic image, making it understandable. There are different kinds of methods used for the implementation of this approach. This paper evaluates the performance of the 3 universal un-warping methods currently applied actively around the world in transforming omni-directional image to panoramic image, namely the pano-mapping table method, discrete geometry method （DGT） and the log-polar mapping method. The algorithm of these methods will first be proposed, and the code will then be generated and be tested on several different omni-directional images. The images converted will then be compared among each other and be evaluated based on their performance on the resolutions, quality, algorithm used, complexity based on Big-O computations, processing time, and finally their data compression rate available for each of the methods. The most preferable un-warping method will then be concluded, taking into considerations all these factors.
基金supported by the National Natural Science Foundation of China(Project Nos.61521002 and 61772298)。
文摘In many applications of computer graphics,art,and design,it is desirable for a user to provide intuitive non-image input,such as text,sketch,stroke,graph,or layout,and have a computer system automatically generate photo-realistic images according to that input.While classically,works that allow such automatic image content generation have followed a framework of image retrieval and composition,recent advances in deep generative models such as generative adversarial networks(GANs),variational autoencoders(VAEs),and flow-based methods have enabled more powerful and versatile image generation approaches.This paper reviews recent works for image synthesis given intuitive user input,covering advances in input versatility,image generation methodology,benchmark datasets,and evaluation metrics.This motivates new perspectives on input representation and interactivity,cross fertilization between major image generation paradigms,and evaluation and comparison of generation methods.
