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In recent years, sensor research has been undergoing a quiet revolution, promising to have a significant impact throughout society that could quite possibly dwarf previous milestones in the information revolution. Realizing the great promise of sensor networks requires more than a mere advance in individual technologies. It relies on many components working(More)
Compressive sampling is a novel framework that exploits sparsity of a signal in a transform domain to perform sampling below the Nyquist rate. In this paper, we apply compressive sampling to significantly reduce the sampling rate of video. A practical system is developed that first splits each video frame into non-overlapping blocks of equal size.(More)
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)
This paper examines the high-rate performance of low-dimensional nested lattice quantizers for the quadratic Gaussian Wyner-Ziv problem, using a pair of nested lattices with the same dimensionality. As the rate increases, the gap increases between the performances of low dimensional nested lattice quantizers and the Wyner-Ziv rate-distortion function. This(More)
We introduce Hamming Codes for Multiple Sources (HCMSs) as a potential solution of perfect Slepian-Wolf (SW) coding for arbitrary number of terminals. Moreover, we study the case with three sources in detail. We present the necessary conditions of a perfect SW code and show that there exists infinite number of HCMSs. Moreover, we show that for perfect SW(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)
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)