As more images and videos are becoming available in compressed formats, researchers have begun designing algorithms for different image operations directly in their domains of representation, leading to faster computation and lower buffer requirements. Image and Video Processing in the Compressed Domain presents the fundamentals, properties, and applications of a variety of image transforms used in image and video compression. It illustrates the development of algorithms for processing images and videos in the compressed domain.
Developing concepts from first principles, the book introduces popular image and video compression algorithms, in particular JPEG, JPEG2000, MPEG-2, MPEG-4, and H.264 standards. It also explores compressed domain analysis and performance metrics for comparing algorithms. The author then elucidates the definitions and properties of the discrete Fourier transform (DFT), discrete cosine transform (DCT), integer cosine transform (ICT), and discrete wavelet transform (DWT). In the subsequent chapters, the author discusses core operations, such as image filtering, color enhancement, image resizing, and transcoding of images and videos, that are used in various image and video analysis approaches. He also focuses on other facets of compressed domain analysis, including video editing operations, video indexing, and image and video steganography and watermarking.
With MATLAB® codes available as a download from the CRC Press website, this book takes you through the steps involved in processing and analyzing compressed videos and images. It covers the algorithms, standards, and techniques used for coding images and videos in compressed formats.
Table of Contents
Image and Video Compression: An Overview
Compression: Generic Approaches
Motivation for Processing in the Compressed Domain
Overview of Different Image and Video Compression Techniques and Standards
Image Compression Techniques
Video Compression Techniques
Examples of a Few Operations in the Compressed Domain
Issues and Performance Measures
Orthogonal Expansion of a Function
Transforms of Discrete Functions
Transforms in 2-D Space
Linear Shift Invariant (LSI) Systems
Discrete LSI Systems
Filtering a Finite Length Sequence
Filtering 2-D Images
Application of Filtering
Processing Colors in the Compressed Domain
Color Saturation and Desaturation
Image Halving and Image Doubling in the Compressed Domain
Resizing with Integral Factors
Resizing with Arbitrary Factors
Inter Ttransforms Conversions
Image Transcoding: JPEG2000 to JPEG
Error Resilient Transcoding
Image and Video Analysis
Image and Video Editing
Image and Video Indexing
A Summary appears at the end of each chapter.
Jayanta Mukhopadhyay is a professor and head of the Department of Computer Science and Engineering and the School of Information Technology at the Indian Institute of Technology in Kharagpur. He has held visiting positions at the University of California-Santa Barbara, the University of Southern California, and the National University of Singapore. He was also a Humboldt Research Fellow at the Technical University of Munich in 2002. Dr. Mukherjee is a senior member of the IEEE and a fellow of the Indian National Academy of Engineering. His research interests encompass image processing, pattern recognition, computer graphics, multimedia systems, and medical informatics.