Publications by authors named "W H Pearlman"

Set partition coding (SPC) has shown tremendous success in image compression. Despite its popularity, the lack of error resilience remains a significant challenge to the transmission of images in error-prone environments. In this paper, we propose a novel data representation called the progressive significance map (prog-sig-map) for error-resilient SPC.

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Constrained storage vector quantization, (CSVQ), introduced by Chan and Gersho (1990, 1991) allows for the stagewise design of balanced tree-structured residual vector quantization codebooks with low encoding and storage complexities. On the other hand, it has been established by Makhoul et al. (1985), Riskin et al.

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An image coding algorithm, Progressive Resolution Coding (PROGRES), for a high-speed resolution scalable decoding is proposed. The algorithm is designed based on a prediction of the decaying dynamic ranges of wavelet subbands. Most interestingly, because of the syntactic relationship between two coders, the proposed method costs an amount of bits very similar to that used by uncoded (i.

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In this paper, we present a two-stage near-lossless compression scheme. It belongs to the class of "lossy plus residual coding" and consists of a wavelet-based lossy layer followed by arithmetic coding of the quantized residual to guarantee a given L(infinity) error bound in the pixel domain. We focus on the selection of the optimum bit rate for the lossy layer to achieve the minimum total bit rate.

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This article presents a lossless compression of volumetric medical images with the improved three-dimensional (3-D) set partitioning in hierarchical tree (SPIHT) algorithm that searches on asymmetric trees. The tree structure links wavelet coefficients produced by 3-D reversible integer wavelet transforms. Experiments show that the lossless compression with the improved 3-D SPIHT gives improvement about 42% on average over two-dimensional techniques and is superior to those of prior results of 3-D techniques.

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