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Détails
Format – détails additionnels: | Online version: Rabbani, Majid, 1955- Digital image compression techniques. Bellingham, Wash., USA : Spie Optical Engineering Press, ©1991 (OCoLC)551705524 |
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Type de document: | Livre |
Tous les auteurs / collaborateurs: |
Majid Rabbani; Paul W Jones |
ISBN: | 0819406481 9780819406484 |
Numéro OCLC: | 23142891 |
Description: | xv, 221 pages : illustrations ; 25 cm. |
Contenu: | I. 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. |
Titre de collection: | Tutorial texts in optical engineering, v. TT 7. |
Responsabilité: | Majid Rabani and Paul W. Jones. |
Résumé:
In 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 techniques 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 reconstructed image quality. For each algorithm, issues such as quality vs. bit rate, implementation complexity, and susceptibility to channel errors are considered.
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