Image analysis – Image compression or coding – Lossless compression
Patent
1997-07-21
1999-05-11
Vu, Kim Yen
Image analysis
Image compression or coding
Lossless compression
382232, 382237, 341 51, G06K9/36
Patent
active
059036761
DESCRIPTION:
BRIEF SUMMARY
BACKGROUND OF THE INVENTION
With rapidly-advancing computer, telecommunication, and digital imaging technologies, there is an astronomical amount of image data for a wide range of applications such as education, entertainment, medical imaging, space exploration, electronic publishing, visual arts, etc. This rapid growth of image data puts punishing burdens on computer storage and visual communication bandwidth. Thus image compression becomes a pressing technical challenge in visual communications and computing, without which it will be difficult to build, deploy, and use cost-effective multimedia information systems.
Lossless compression is a form of compression where an image can be reconstructed without any loss of information. Lossless image compression is required by medical imaging, satellite/aerial imaging, image archiving, preservation of precious art work and documents, the press, or any applications demanding ultra high image fidelity. Furthermore, lossless image coding is the necessary last step of many lossy image compression systems, such as lossless compression of codeword indices in vector quantization (VQ), and lossless compression of transform coefficients in Discrete Cosine Transform (DCT) and wavelet/subband-based coding.
There exists a large body of literature on lossless image compression algorithms and systems, such as the IBM Q-coder, and JPEG lossless coder. Among notable patents and publications are the US patents and research publications listed below: IT-27. Images--S. Todd, G. Langdon, and J. Rissanen, 1985, IBM J. Res. & Develop., vol. 29. Modelling--R. Arps, M. Weinberger, T. Truong, and J. Rissanen, Proc. of the Picture coding Symposium, Sacramento, September 1994. and E. Seiler, Proc. of 1992 Data Compression Conf. Howard and J. Vitter, 1992, Info. Proc. & Manag., vol. 28.
The currently achievable lossless compression ratio is still modest, being typically from 1.5:1 to 2.5:1. For instance, in contrast to the success of JPEG's lossy compression standard, the current JPEG's lossless compression standard has sufficiently poor coding efficiency that it is seldom used in practice.
In 1994, ISO and JPEG solicited for proposals for the next international standard for lossless image compression. The present invention is a result of the inventors' response to the ISO solicitation. The lead inventor Xiaolin Wu, developed a context-based, adaptive, lossless image coding and decoding technique (herein CALIC). Among nine proposals that were submitted to ISO for its initial evaluation as candidates for the lossless image compression standard in 1995, the present CALIC system ranked first according to a criterion that accounts for both coding efficiency and algorithm simplicity.
EP A 0 613 290 entitled METHOD AND APPARATUS FOR BINARY IMAGE DATA COMPRESSION published on Aug. 31, 1994 describes a method and apparatus for lossless compression of binary images only. The abstract and specification of EP A 0 613 290 mention that the method and apparatus are applicable to "photographs" and "mixed binary images". However, it is apparent that the photographs referred to are digitally half-toned photographs and not true continuous toned images. The method and apparatus of EP A 0 613 290 only encode binary image data and d o not provide for compression of continuous tone images, graphics, or mixtures of binary images with continuous tone images, and graphics.
EP A 0 547 528 entitled METHOD AND ASSOCIATED APPARATUS FOR ENCODING BIT PLANES published on Jun. 23, 1993 describes a scheme for lossless image compression by bit-plane encoding. Bit plane encoding has significant known disadvantages.
P. E. Tischer et al. Context-based Lossless Image Compression 8199 The Computer Journal vol. 36 no. 1 pp. 68-77 (1993) provides a general academic treatment of the subject of context based lossless image compression.
Known prior art on lossless compression of continuous-tone images is based on the principle of predictive coding. An image is traversed, and pixels are encoded in a fixed order, typically in raster s
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P.E. Tisher et al., "Context-Based Lossless Image Compression," The Computer Journal, vol. 36, No. 1, 1993, pp. 68-77.
Memon Nasir
Wu Xiaolin
Allen Kenneth R.
Nguyen Jimmy D.
The Chinese University of Hong Kong
Vu Kim Yen
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