A New Technique for Lossless Compression of Color Images Based on Hierarchical Prediction, Inversion and Context Adaptive Coding

This work introduces a new technique for lossless compression of color images. The technique is composed of first transforming an RGB image into luminance and chrominance domain (Y CuCv). Then, the luminance channel Y is compressed with a context-based, adaptive, lossless image coding technique (CAL...

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Bibliographic Details
Main Authors: Koc, Basar, Arnavut, Ziya, Sarkar, Dilip, Kocak, Huseyin
Format: Conference Proceeding
Language:English
Subjects:
Adaptive coding
Biomedical imaging
BWIC
BWT
CALIC
Color
Image coding
JPEG 2000
Prediction algorithms
Transform coding
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Summary:This work introduces a new technique for lossless compression of color images. The technique is composed of first transforming an RGB image into luminance and chrominance domain (Y CuCv). 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 by Kim and Cho, Burrows-Wheeler Inversion Coder (BWIC) or JPEG 2000 is used to compress of the chrominance channels Cu and Cv. 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, JPEG 2000, LOCO-I, BPG(HEVC), and the previously proposed hierarchical prediction and context adaptive coding technique LCIC.
ISSN:2375-0359
DOI:10.1109/DCC.2019.00096