Modern Image Quality Assessment

Modern Image Quality Assessment

Zhou Wang, Alan C. Bovik
ISBN: 9781598290226 | PDF ISBN: 9781598290233
Copyright © 2006 | 156 Pages | Publication Date: 01/01/2006

BEFORE YOU ORDER: You may have Academic or Corporate access to this title. Click here to find out: 10.2200/S00010ED1V01Y200508IVM003

Ordering Options: Paperback $35.00   E-book $28.00   Paperback & E-book Combo $43.75


Why pay full price? Members receive 15% off all orders.
Learn More Here

Read Our Digital Content License Agreement (pop-up)

Purchasing Options:


This 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.

Table of Contents

Introduction
Bottom-Up Approaches for Full-Reference Image Quality Assessment
Top-Down Approaches for Full-Reference Image Quality Assessment
No-Reference Image Quality Assessment
Reduced-Reference Image Quality Assessment
Conclusion

About the Author(s)

Zhou Wang, The University of Texas at Arlington

Alan C. Bovik, The University of Texas at Austin

Reviews
Browse by Subject
Case Studies in Engineering
ACM Books
IOP Concise Physics
SEM Books
0 items
LATEST NEWS

Newsletter
Note: Registered customers go to: Your Account to subscribe.

E-Mail Address:

Your Name: