Lossy Image Compression

Domain Decomposition-Based Algorithms

Nonfiction, Computers, Advanced Computing, Engineering, Optical Data Processing, Application Software, Computer Graphics, General Computing
Cover of the book Lossy Image Compression by M.V. Prasad, K K Shukla, Springer London
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Author: M.V. Prasad, K K Shukla ISBN: 9781447122180
Publisher: Springer London Publication: August 28, 2011
Imprint: Springer Language: English
Author: M.V. Prasad, K K Shukla
ISBN: 9781447122180
Publisher: Springer London
Publication: August 28, 2011
Imprint: Springer
Language: English

Image compression is concerned with minimization of the number of information carrying units used to represent an image. Lossy compression techniques incur some loss of information which is usually imperceptible. In return for accepting this distortion, we obtain much higher compression ratios than is possible with lossless compression. Salient features of this book include: four new image compression algorithms and implementation of these algorithms; detailed discussion of fuzzy geometry measures and their application in image compression algorithms; new domain decomposition based algorithms using image quality measures and study of various quality measures for gray scale image compression; compression algorithms for different parallel architectures and evaluation of time complexity for encoding on all architectures; parallel implementation of image compression algorithms on a cluster in Parallel Virtual Machine (PVM) environment.

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Image compression is concerned with minimization of the number of information carrying units used to represent an image. Lossy compression techniques incur some loss of information which is usually imperceptible. In return for accepting this distortion, we obtain much higher compression ratios than is possible with lossless compression. Salient features of this book include: four new image compression algorithms and implementation of these algorithms; detailed discussion of fuzzy geometry measures and their application in image compression algorithms; new domain decomposition based algorithms using image quality measures and study of various quality measures for gray scale image compression; compression algorithms for different parallel architectures and evaluation of time complexity for encoding on all architectures; parallel implementation of image compression algorithms on a cluster in Parallel Virtual Machine (PVM) environment.

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