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100   $a19910124d1991      uy         0
101 0 $aeng
135   $aurbn||||m|||a
181   $ctxt
182   $cc
183   $acr
200 10$aDigital image compression techniques /$fMajid Rabani, Paul W. Jones
210   $aBellingham, Wash. $cSpie Optical Engineering Press$dc1991
215   $a1 online resource (236 p.)
225 1 $aTutorial texts in optical engineering ;$vv. TT 7
300   $aDescription based upon print version of record.
311 08$a9780819406484 
311 08$a0819406481 
320   $aIncludes bibliographical references.
327   $aI. Background -- Digital images and image compression -- II. Information theory concepts -- Source models and entropy -- Variable-length codes -- Entropy estimation and lossless compression -- Rate-distortion theory and lossy compression -- III. Lossless compression techniques -- Introduction -- Bit plane encoding -- Lossy plus lossless residual encoding -- IV. Lossy compression techniques -- Introduction -- Lossy predictive coding -- Transform coding -- Block truncation coding -- Vector quantization -- Subband coding -- Hierarchical coding -- Choosing a lossy compression technique -- Appendix Compression of color images.
330   $aIn order to utilize digital images effectively, specific techniques are needed to reduce the number of bits required for their representation. This Tutorial Text provides the groundwork for understanding these image compression tecniques and presents a number of different schemes that have proven useful. The algorithms discussed in this book are concerned mainly with the compression of still-frame, continuous-tone, monochrome and color images, but some of the techniques, such as arithmetic coding, have found widespread use in the compression of bilevel images. Both lossless (bit-preserving) and lossy techniques are considered. A detailed description of the compression algorithm proposed as the world standard (the JPEG baseline algorithm) is provided. The book contains approximately 30 pages of reconstructed and error images illustrating the effect of each compression technique on a consistent image set, thus allowing for a direct comparison of bit rates and reconstucted image quality. For each algorithm, issues such as quality vs. bit rate, implementation complexity, and susceptibility to channel errors are considered.
410  0$aTutorial texts in optical engineering ;$vv. TT 7.
606   $aImage processing$xDigital techniques
606   $aCoding theory
606   $aImage compression$xData processing
615  0$aImage processing$xDigital techniques.
615  0$aCoding theory.
615  0$aImage compression$xData processing.
676   $a621.36/7
700   $aRabbani$b Majid$f1955-$028157
701   $aJones$b Paul W.$f1958-$01822017
712 02$aSociety of Photo-optical Instrumentation Engineers.
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9911004814403321
996   $aDigital image compression techniques$94388019
997   $aUNINA