東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Quality assessment of visual content

Gu, Ke.

FindBook

Google Book

Amazon

博客來

Quality assessment of visual content

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Quality assessment of visual content/ by Ke Gu, Hongyan Liu, Chengxu Zhou.
作者:	Gu, Ke.
其他作者:	Liu, Hongyan.
出版者:	Singapore :Springer Nature Singapore : : 2022.,
面頁冊數:	xvii, 242 p. :ill. (chiefly color), digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Computer graphics - Quality control. -
電子資源:	https://doi.org/10.1007/978-981-19-3347-9
ISBN:	9789811933479

Quality assessment of visual content
Gu, Ke.

Quality assessment of visual content[electronic resource] /by Ke Gu, Hongyan Liu, Chengxu Zhou. - Singapore :Springer Nature Singapore :2022. - xvii, 242 p. :ill. (chiefly color), digital ;24 cm. - Advances in computer vision and pattern recognition,2191-6594. - Advances in computer vision and pattern recognition..

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.

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.

ISBN: 9789811933479

Standard No.: 10.1007/978-981-19-3347-9doiSubjects--Topical Terms:

3607127
Computer graphics
--Quality control.

LC Class. No.: T385 / .G8 2022

Dewey Class. No.: 006.6

Quality assessment of visual content
LDR:03011nmm a2200361 a 4500 001 2304697
003 DE-He213
005 20221019040309.0
006 m d
007 cr nn 008maaau
008 230409s2022 si s 0 eng d
020 $a 9789811933479 $q (electronic bk.)
020 $a 9789811933462 $q (paper)
024 7 $a 10.1007/978-981-19-3347-9 $2 doi
035 $a 978-981-19-3347-9
040 $a GP $c GP
041 0 $a eng
050 4 $a T385 $b .G8 2022
072 7 $a TJF $2 bicssc
072 7 $a UYT $2 bicssc
072 7 $a COM016000 $2 bisacsh
072 7 $a TJF $2 thema
072 7 $a UYT $2 thema
082 0 4 $a 006.6 $2 23
090 $a T385 $b .G896 2022
100 1 $a Gu, Ke. $3 3607125
245 1 0 $a Quality assessment of visual content $h [electronic resource] / $c by Ke Gu, Hongyan Liu, Chengxu Zhou.
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2022.
300 $a xvii, 242 p. : $b ill. (chiefly color), digital ; $c 24 cm.
490 1 $a Advances in computer vision and pattern recognition, $x 2191-6594
505 0 $a 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.
520 $a 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.
650 0 $a Computer graphics $x Quality control. $3 3607127
650 1 4 $a Image Processing. $3 891209
650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 890871
650 2 4 $a Computer Vision. $3 3538524
700 1 $a Liu, Hongyan. $3 1086487
700 1 $a Zhou, Chengxu. $3 3607126
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Advances in computer vision and pattern recognition. $3 1567575
856 4 0 $u https://doi.org/10.1007/978-981-19-3347-9
950 $a Computer Science (SpringerNature-11645)