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We study lossy-to-lossless compression of medical volumetric data using three-dimensional (3-D) integer wavelet transforms. To achieve good lossy coding performance, it is important to have transforms that are unitary. In addition to the lifting approach, we first introduce a general 3-D integer wavelet packet transform structure that allows implicit bit(More)
—We study the problem of packetizing embedded multimedia bitstreams to improve the error resilience of source (compression) codes. This problem is important because of the increasing popularity of embedded compression methodology [1]–[7] and its suitability for scalable streaming media [8], [9] over IP or/and mobile IP. We study various packetization(More)
This paper considers TCQ and LDPC codes for the quadratic Gaussian Wyner-Ziu problem. After TCQ of the source input X, LDPC codes are used to implement Slepian-Wolf coding of the quantized source input Q(X) given the side information Y at the decoder. Assuming ideal Slepian-Wolf coding in the sense of achieving ,the theoretical limit H (Q (X) I Y) , it is(More)
—Belief propagation (BP) is a powerful algorithm to decode low-density parity check (LDPC) codes over additive white Gaussian noise (AWGN) channels. However, the traditional BP algorithm cannot adapt efficiently to the statistical change of SNR in an AWGN channel. This paper proposes an adaptive scheme that incorporates a particle filtering (PF) algorithm(More)
Distributed source coding (DSC) refers to separate compression and joint decompression of mutually correlated sources. Though theoretical foundations were set more than thirty years ago, driven by applications such as wireless sensor networks, video surveillance, and multiview video, DSC has over the past few years become a very active research area. This(More)
—In this paper, we propose a system using video cameras to perform vehicle identification. We tackle this problem by reconstructing an input by using multiple linear regression models and compressed sensing, which provide new ways to deal with three crucial issues in vehicle identification , namely, feature extraction, online vehicle identification database(More)
The purpose of this study was to develop and assess a new quantitative four-view mammographic image feature based fusion model to predict the near-term breast cancer risk of the individual women after a negative screening mammography examination of interest. The dataset included fully-anonymized mammograms acquired on 870 women with two sequential(More)