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RT Book, Whole SR Electronic DC OPAC T1 Quality Assessment of Visual Content / by Ke Gu, Hongyan Liu, Chengxu Zhou T2 Advances in Computer Vision and Pattern Recognition. ISSN:21916594 A1 Gu, Ke A1 Liu, Hongyan A1 Zhou, Chengxu A1 SpringerLink (Online service) YR 2022 FD 2022 SP XVII, 242 p. 75 illus., 66 illus. in color K1 Image processing K1 Image processing -- Digital techniques K1 Computer vision K1 Image Processing K1 Computer Imaging, Vision, Pattern Recognition and Graphics K1 Computer Vision ED 1st ed. 2022. PB Springer Nature Singapore : Imprint: Springer PP Singapore SN 9789811933479 LA English (英語) CL LCC:TA1637-1638 CL DC23:621.382 NO Chapter 1. Introduction -- Chapter 2. Quality Assessment of Screen Content Images -- Chapter 3. Quality Assessment of 3D-Synthesized Images -- Chapter 4. Quality Assessment of Sonar Images -- Chapter 5. Quality Assessment of Enhanced Images -- Chapter 6. Quality Assessment of Light-Field Image -- Chapter 7. Quality Assessment of Virtual Reality Images -- Chapter 8. Quality Assessment of Super-Resolution Images NO This book provides readers with a comprehensive review of image quality assessment technology, particularly applications on screen content images, 3D-synthesized images, sonar images, enhanced images, light-field images, VR images, and super-resolution images. It covers topics containing structural variation analysis, sparse reference information, multiscale natural scene statistical analysis, task and visual perception, contour degradation measurement, spatial angular measurement, local and global assessment metrics, and more. All of the image quality assessment algorithms of this book have a high efficiency with better performance compared to other image quality assessment algorithms, and the performance of these approaches mentioned above can be demonstrated by the results of experiments on real-world images. On the basis of this, those interested in relevant fields can use the results obtained through these quality assessment algorithms for further image processing. The goal of this book is to facilitate the use of these image quality assessment algorithms by engineers and scientists from various disciplines, such as optics, electronics, math, photography techniques and computation techniques. The book can serve as a reference for graduate students who are interested in image quality assessment techniques, for front-line researchers practicing these methods, and for domain experts working in this area or conducting related application development NO HTTP:URL=https://doi.org/10.1007/978-981-19-3347-9 NO 書誌ID=EB00002053; LK [E Book]https://doi.org/10.1007/978-981-19-3347-9 OL 30