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Block truncation coding using pattern fitting

✍ Scribed by Bibhas Chandra Dhara; Bhabatosh Chanda


Book ID
103878653
Publisher
Elsevier Science
Year
2004
Tongue
English
Weight
587 KB
Volume
37
Category
Article
ISSN
0031-3203

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✦ Synopsis


Block truncation coding (BTC) divides an image into blocks having given size and then encodes each block by two representative gray levels and a bit-pattern. In this work a modiΓΏed scheme of BTC is proposed where the computed representative gray levels are the bias and the contrast in each block. Secondly, instead of determining bit-pattern for each block, an optimum bit-pattern is selected from a pattern-book. Thus the index of the optimum pattern is used to encode in lieu of the explicit pattern. Thirdly, if the contrast is low the block is assumed to be smooth and bit-pattern is not required to reconstruct the block. This leads to signiΓΏcant reduction in bit-rate (bpp). Finally, the contrast component and the predictive residual of the bias component are entropy coded to achieve further reduction in bpp. Performance of the proposed scheme is measured in terms of peak-signal-to-noise ratio and bpp, and is compared with other recently reported methods.


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✍ K.W. Chan; K.L. Chan πŸ“‚ Article πŸ“… 2001 πŸ› Elsevier Science 🌐 English βš– 763 KB

Block truncation coding (BTC) is very attractive for real-time image coding at moderate bit-rate due to its low computation and storage demands. One major artefact of this image compression technique is edge raggedness. Modi"cations are mainly in two areas: bit-rate reduction and improvement of the