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16 September 2019 Technique for lossless compression of color images based on hierarchical prediction, inversion, and context adaptive coding
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Abstract

Among the variety of multimedia formats, color images play a prominent role. A technique for lossless compression of color images is introduced. The technique is composed of first transforming a red, green, and blue image into luminance and chrominance domain (YCuCv). Then, the luminance channel Y is compressed with a context-based, adaptive, lossless image coding technique (CALIC). After processing the chrominance channels with a hierarchical prediction technique that was introduced earlier, Burrows–Wheeler inversion coder or JPEG 2000 is used in compression of those Cu and Cv channels. It is demonstrated that, on a wide variety of images, particularly on medical images, the technique achieves substantial compression gains over other well-known compression schemes, such as CALIC, M-CALIC, Better Portable Graphics, JPEG-LS, JPEG 2000, and the previously proposed hierarchical prediction and context-adaptive coding technique LCIC.

© 2019 SPIE and IS&T 1017-9909/2019/$28.00 © 2019 SPIE and IS&T
Basar Koc, Ziya Arnavut, Dilip Sarkar, and Hüseyin Koçak "Technique for lossless compression of color images based on hierarchical prediction, inversion, and context adaptive coding," Journal of Electronic Imaging 28(5), 053007 (16 September 2019). https://doi.org/10.1117/1.JEI.28.5.053007
Received: 2 May 2019; Accepted: 27 August 2019; Published: 16 September 2019
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