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Digital Image Compression Techniques (SPIE Tutorial Text Vol. TT07) (Tutorial Texts in Optical Engineering) [Paperback]

Majid Rabbani (Author), Paul W. Jones (Author)

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Book Description

February 1, 1991 0819406481 978-0819406484
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 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.

Contents:
- Digital Images and Image Compression
- Source Models and Entropy
- Variable-Length Codes
- Entropy Estimation and Lossless Compression
- Rate-Distortion Theory and Lossy Compression
- Bit Plane Encoding
- Lossless Predictive Coding
- Lossy Plus Lossless Residual Encoding
- Lossy Predictive Coding
- Transform Coding
- Block Truncation Coding
- Vector Quantization
- Subband Coding
- Hierarchical Coding
- Choosing a Lossy Compression Technique
- Compression of Color Images


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Inside This Book (learn more)
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
digital image compression techniques, vector quantization, transform coding, lossless predictive coding, lossy compression techniques, code bit planes, possible image vectors, two reconstruction levels, original source symbol, previous pixel values, adjoint source, local codebook, global codebook, two test images, block truncation coding, normalization array, differential image, reconstructed image quality, lossy scheme, neighboring contexts, binary arithmetic coder, prediction image, resulting bit rate, quantizer levels, initial codebook
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Lossy Predictive Coding, Special Issue, Technique Bit, New York, Englewood Cliffs, Academic Press, Bit Plane Encoding, Hierarchical Coding
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