Full Reference Image Quality Metrics
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Modern Image Quality Assessment
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.
Camera Image Quality Benchmarking
Author: Jonathan B. Phillips
language: en
Publisher: John Wiley & Sons
Release Date: 2018-01-09
The essential guide to the entire process behind performing a complete characterization and benchmarking of cameras through image quality analysis Camera Image Quality Benchmarking contains the basic information and approaches for the use of subjectively correlated image quality metrics and outlines a framework for camera benchmarking. The authors show how to quantitatively compare image quality of cameras used for consumer photography. This book helps to fill a void in the literature by detailing the types of objective and subjective metrics that are fundamental to benchmarking still and video imaging devices. Specifically, the book provides an explanation of individual image quality attributes and how they manifest themselves to camera components and explores the key photographic still and video image quality metrics. The text also includes illustrative examples of benchmarking methods so that the practitioner can design a methodology appropriate to the photographic usage in consideration. The authors outline the various techniques used to correlate the measurement results from the objective methods with subjective results. The text also contains a detailed description on how to set up an image quality characterization lab, with examples where the methodological benchmarking approach described has been implemented successfully. This vital resource: Explains in detail the entire process behind performing a complete characterization and benchmarking of cameras through image quality analysis Provides best practice measurement protocols and methodologies, so readers can develop and define their own camera benchmarking system to industry standards Includes many photographic images and diagrammatical illustrations to clearly convey image quality concepts Champions benchmarking approaches that value the importance of perceptually correlated image quality metrics Written for image scientists, engineers, or managers involved in image quality and evaluating camera performance, Camera Image Quality Benchmarking combines knowledge from many different engineering fields, correlating objective (perception-independent) image quality with subjective (perception-dependent) image quality metrics.
Handbook of Image and Video Processing
55% new material in the latest edition of this "must-have for students and practitioners of image & video processing!This Handbook is intended to serve as the basic reference point on image and video processing, in the field, in the research laboratory, and in the classroom. Each chapter has been written by carefully selected, distinguished experts specializing in that topic and carefully reviewed by the Editor, Al Bovik, ensuring that the greatest depth of understanding be communicated to the reader. Coverage includes introductory, intermediate and advanced topics and as such, this book serves equally well as classroom textbook as reference resource. • Provides practicing engineers and students with a highly accessible resource for learning and using image/video processing theory and algorithms • Includes a new chapter on image processing education, which should prove invaluable for those developing or modifying their curricula • Covers the various image and video processing standards that exist and are emerging, driving today's explosive industry • Offers an understanding of what images are, how they are modeled, and gives an introduction to how they are perceived • Introduces the necessary, practical background to allow engineering students to acquire and process their own digital image or video data • Culminates with a diverse set of applications chapters, covered in sufficient depth to serve as extensible models to the reader's own potential applications About the Editor... Al Bovik is the Cullen Trust for Higher Education Endowed Professor at The University of Texas at Austin, where he is the Director of the Laboratory for Image and Video Engineering (LIVE). He has published over 400 technical articles in the general area of image and video processing and holds two U.S. patents. Dr. Bovik was Distinguished Lecturer of the IEEE Signal Processing Society (2000), received the IEEE Signal Processing Society Meritorious Service Award (1998), the IEEE Third Millennium Medal (2000), and twice was a two-time Honorable Mention winner of the international Pattern Recognition Society Award. He is a Fellow of the IEEE, was Editor-in-Chief, of the IEEE Transactions on Image Processing (1996-2002), has served on and continues to serve on many other professional boards and panels, and was the Founding General Chairman of the IEEE International Conference on Image Processing which was held in Austin, Texas in 1994.* No other resource for image and video processing contains the same breadth of up-to-date coverage* Each chapter written by one or several of the top experts working in that area* Includes all essential mathematics, techniques, and algorithms for every type of image and video processing used by electrical engineers, computer scientists, internet developers, bioengineers, and scientists in various, image-intensive disciplines