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Lossy Image Compression

Name: Lossy Image Compression
Brand: Springer London Ltd
SKU: 9781447122173
Price: 277.38 RON
Availability: InStock

Domain Decomposition-Based Algorithms

Autor: K.K. Shukla, M.V. Prasad

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Legare: Carte broșată

Editura: Springer London Ltd

Disponibilitate: În depozitul extern

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277.38 lei

Good quality digital images have high storage and bandwidth requirements. In modern times, with incr...

Informații despre carte

Autor

K.K. Shukla, M.V. Prasad

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2011

Pagini

EAN

9781447122173

ISBN

1447122178

Enbook ID

01425671

Editura

Springer London Ltd

Greutate

172

Dimensiuni

155 x 235 x 7

Descriere completă

Good quality digital images have high storage and bandwidth requirements. In modern times, with increasing user expectation for image quality, efficient compression is necessary to keep memory and transmission time within reasonable limits.§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.§This book will be of interest to graduate students, researchers and practicing engineers looking for new image compression techniques that provide good perceived quality in digital images with higher compression ratios than is possible with conventional algorithms.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.Good quality digital images have high storage and bandwidth requirements. In modern times, with increasing user expectation for image quality, efficient compression is necessary to keep memory and transmission time within reasonable limits.§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 algorithmsDetailed discussion of fuzzy geometry measures and their application in image compression algorithmsNew domain decomposition based algorithms using image quality measures and study of various quality measures for gray scale image compressionCompression algorithms for different parallel architectures and evaluation of time complexity for encoding on all architecturesParallel implementation of image compression algorithms on a cluster in Parallel Virtual Machine (PVM) environment.This book will be of interest to graduate students, researchers and practicing engineers looking for new image compression techniques that provide good perceived quality in digital images with higher compression ratios than is possible with conventional algorithms.