• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.756-761
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• 1998

This paper describes an in-line lossless data compression method using adaptive binary arithmetic coding. To achieve better compression efficiency , we employ an adaptive fuzzy -tuning modeler, which uses fuzzy inference to deal with the problem of conditional probability estimation. The design is simple, fast and suitable for VLSI implementation because we adopt the table -look-up approach. As compared with the out-comes of other lossless coding schemes, our results are good and satisfactory for various types of source data.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.349-356
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• 1997

In this paper, we propose the lossless coding: scheme for progressive transmission of medical images. The input image is decomposed by the proposed fast adaptive subband decomposition method which is suited for a lossless coding. The decomposed images are coded by an arithmetic coder with two conditioning pixels, and the conditioning pixels are selected differently according to the property of the subbands. The conditioning contexts are usually quantized to reduce the conditional state, and the optimization method of quantization is proposed For the purpose of improving compression ratio in this paper. The proposed lossless coding scheme provides the asymmetric structure of cosec and results in better compression ability than the JPEC lossless coding[ 1 ].

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.339-348
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• 1997

In this paper, we propose a coding method to improve compression efficiency for MR image. This can be achieved by combining coding scheme and segmentation scheme which removes noisy background region, which is meaningless for diagnosis in the MR image. In segmentation algoritm, we use full-resolution wavelet transform to extract features of regions in image and Kohonen self-organizing map to classify the features. The subsequent wavelet coder encodes only diagnostically significant foreground regions refering to segmentation map. Our proposed algorithm provides about 15% of bit rate reduction when compared with the same coder which is not combined with segmentation scheme. And the proposed scheme shows better reconstructed image quality than JPEG at the same compression ratio.