Modern Image Quality Assessment

Modern Image Quality Assessment
Author :
Publisher : Springer Nature
Total Pages : 146
Release :
ISBN-10 : 9783031022388
ISBN-13 : 3031022386
Rating : 4/5 (88 Downloads)

Book Synopsis Modern Image Quality Assessment by : Zhou Wang

Download or read book Modern Image Quality Assessment written by Zhou Wang and published by Springer Nature. This book was released on 2022-06-01 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Lecture book is about objective image quality assessment—where the aim is to provide computational models that can automatically predict perceptual image quality. The early years of the 21st century have witnessed a tremendous growth in the use of digital images as a means for representing and communicating information. A considerable percentage of this literature is devoted to methods for improving the appearance of images, or for maintaining the appearance of images that are processed. Nevertheless, the quality of digital images, processed or otherwise, is rarely perfect. Images are subject to distortions during acquisition, compression, transmission, processing, and reproduction. To maintain, control, and enhance the quality of images, it is important for image acquisition, management, communication, and processing systems to be able to identify and quantify image quality degradations. The goals of this book are as follows; a) to introduce the fundamentals of image quality assessment, and to explain the relevant engineering problems, b) to give a broad treatment of the current state-of-the-art in image quality assessment, by describing leading algorithms that address these engineering problems, and c) to provide new directions for future research, by introducing recent models and paradigms that significantly differ from those used in the past. The book is written to be accessible to university students curious about the state-of-the-art of image quality assessment, expert industrial R&D engineers seeking to implement image/video quality assessment systems for specific applications, and academic theorists interested in developing new algorithms for image quality assessment or using existing algorithms to design or optimize other image processing applications.


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