Lossless image coding via adaptive linear prediction and classification

• Published in: Proceedings of the IEEE Vol. 88; no. 11; pp. 1790 - 1796
• Main Authors: Motta, G., Storer, J.A., Carpentieri, B.
• Format: Journal Article Conference Proceeding
• Language: English
• Published: New York, NY IEEE 2000; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive algorithm; Applied sciences; Arithmetic; Categories; Classification; Compressors; Computational complexity; Computers in experimental physics; Data compression; Entropy; Entropy coding; Exact sciences and technology; Fundamental areas of phenomenology (including applications); Gradient methods; Image coding; Image forming and processing; Image processing; Imaging and optical processing; Information, signal and communications theory; Instruments, apparatus, components and techniques common to several branches of physics and astronomy; Linear prediction; Lossless; Optics; Performance loss; Physics; Signal processing; State of the art; Telecommunications and information theory; Testing; Image coding; Arithmetic codes; Image processing; Data compression; Classification; Theoretical study; Linear predictive coding; Gradient method; Adaptive coding
• ISSN: 0018-9219; 1558-2256
• DOI: 10.1109/5.892714

In past years, there have been several improvements in lossless image compression. All the recently proposed state-of-the-art lossless image compressors can be roughly divided into two categories: single and double-pass compressors. Linear prediction is rarely used in the first category, while TMW, a state-of-the-art double-pass image compressor, relies on linear prediction for its performance. We propose a single-pass adaptive algorithm that uses context classification and multiple linear predictors, locally optimized on a pixel-by-pixel basis. Locality is also exploited in the entropy coding of the prediction error. The results we obtained on a test set of several standard images are encouraging. On the average, our ALPC obtains a compression ratio comparable to CALIC while improving on some images.