Shukla K.K., Prasad M.V. Lossy Image Compression. Domain Decomposition-Based Algorithms

Springer, 2011. — 102 p.Image data compression is concerned with minimization of the number of information carrying units used to represent an image. Image compression schemes can be divided into two broad classes: lossless compression schemes and lossy compression schemes. Lossless compression techniques, as their name implies aim at exact reconstruction and involve no loss of information. Lossy compression techniques accept some loss of information, therefore images compressed using a lossy technique cannot be reconstructed exactly. The distortion in the image caused by lossy compression may be imperceptible to humans and we obtain much higher compression ratios than is possible with lossless compression. Lossy compression scheme can be further divided into three major categories: 1. Transform coding, 2. Fractal image compression, and 3. Domain Decomposition. Joint Photographic Expert Group (JPEG), JPEG2000, Binary Tree Triangular Coding (BTTC) etc. are the examples of lossy image compression methods. This book describes five new domain decomposition based lossy image compression algorithms, evaluation of their performance and their parallel implementation.Tree Triangular Coding Image Compression Algorithms
Image Compression Using Quality Measures
Parallel Image Compression Algorithms
Conclusions and Future Directions