Optimal Coding of Quantized Laplacian Sources for Predictive Image Compression
Journal of Mathematical Imaging and Vision
Asymptotically Optimal Scalable Coding for Minimum Weighted Mean Square Error
DCC '01 Proceedings of the Data Compression Conference
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Journal of Multivariate Analysis
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IEEE Transactions on Circuits and Systems for Video Technology
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IEEE Transactions on Information Theory
Quantizer offset selection for improved requantization transcoding
Image Communication
Journal of Visual Communication and Image Representation
Very low complexity low rate image coding for the wireless endoscope
Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies
A quantization theoretic perspective on simulcast and layered multicast optimization
IEEE/ACM Transactions on Networking (TON)
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This paper presents solutions to the entropy-constrained scalar quantizer (ECSQ) design problem for two sources commonly encountered in image and speech compression applications: sources having the exponential and Laplacian probability density functions. We use the memoryless property of the exponential distribution to develop a new noniterative algorithm for obtaining the optimal quantizer design. We show how to obtain the optimal ECSQ either with or without an additional constraint on the number of levels in the quantizer. In contrast to prior methods, which require a multidimensional iterative solution of a large number of nonlinear equations, the new method needs only a single sequence of solutions to one-dimensional nonlinear equations (in some Laplacian cases, one additional two-dimensional solution is needed). As a result, the new method is orders of magnitude faster than prior ones. We show that as the constraint on the number of levels in the quantizer is relaxed, the optimal ECSQ becomes a uniform threshold quantizer (UTQ) for exponential, but not for Laplacian sources. We then further examine the performance of the UTQ and optimal ECSQ, and also investigate some interesting alternatives to the UTQ, including a uniform-reconstruction quantizer (URQ) and a constant dead-zone ratio quantizer (CDZRQ)