Lossless compression of color mosaic images

• Published in: IEEE transactions on image processing Vol. 15; no. 6; pp. 1379 - 1388
• Main Authors: Zhang, Ning, Wu, Xiaolin
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.06.2006; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Applied sciences; Bandwidth; Codecs; Coding, codes; Color; Colorimetry - methods; Compressing; Computer Communication Networks; Computer Graphics; Computer Simulation; Context quantization; Data Compression - methods; Data Interpretation, Statistical; Decorrelation; digital camera; Digital cameras; entropy coding; Exact sciences and technology; Image coding; image compression; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Image processing; Image quality; Information, signal and communications theory; Lossless; Models, Statistical; Mosaics; Sampling, quantization; Signal and communications theory; Signal processing; Signal Processing, Computer-Assisted; Signal representation. Spectral analysis; Signal, noise; Spectra; Telecommunications and information theory; Transforms; Wavelet; Wavelet domain; Wavelet packets; Wavelet transforms; Performance evaluation; Lossless circuit; Spectral method; Image processing; entropy coding; Redundancy; Data compression; Entropy codes; Lossless compression; Image compression; Color image; Wavelets; digital camera; Image coding; Codec; Wavelet transformation; Signal quantization; Signal processing; Mosaicism; Context quantization; Decorrelation; Signal analysis
• ISSN: 1057-7149; 1941-0042
• DOI: 10.1109/TIP.2005.871116

Lossless compression of color mosaic images poses a unique and interesting problem of spectral decorrelation of spatially interleaved R, G, B samples. We investigate reversible lossless spectral-spatial transforms that can remove statistical redundancies in both spectral and spatial domains and discover that a particular wavelet decomposition scheme, called Mallat wavelet packet transform, is ideally suited to the task of decorrelating color mosaic data. We also propose a low-complexity adaptive context-based Golomb-Rice coding technique to compress the coefficients of Mallat wavelet packet transform. The lossless compression performance of the proposed method on color mosaic images is apparently the best so far among the existing lossless image codecs.