Fundamentals of digital image processing
Fundamentals of digital image processing
Digital Coding of Waveforms: Principles and Applications to Speech and Video
Digital Coding of Waveforms: Principles and Applications to Speech and Video
Code and Parse Trees for Lossless Source Encoding
SEQUENCES '97 Proceedings of the Compression and Complexity of Sequences 1997
Efficient scalar quantization of exponential and Laplacian random variables
IEEE Transactions on Information Theory
Optimal prefix codes for sources with two-sided geometric distributions
IEEE Transactions on Information Theory
Coding of sources with two-sided geometric distributions and unknown parameters
IEEE Transactions on Information Theory
Transform coding with integer-to-integer transforms
IEEE Transactions on Information Theory
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This paper discusses the optimal coding of uniformly quantized Laplacian sources. The techniques known for designing optimal codes for sources with infinite alphabets are used for the quantized Laplacian sources which have probability mass functions with two geometrically decaying tails. Due to the simple parametric model of the source distribution the Huffman iterations are possible to be carried on analytically, using the concept of reduced source, and the final codes are obtained as a sequence of very simple arithmetic operations, avoiding the need to store coding tables. Comparing three uniform quantizers, we find one which consistently outperforms the others in the rate-distortion sense. We foresee for the newly introduced codes an important area of applications in low complexity lossy image coding, since similar codes, designed for two-sided geometrical sources, became the basic tools used in JPEG-LS lossless image compression.