A chip-set for lossless image compression

Shah, Imran; Akiwumi-Assani, O.; Johnson, B. Connor

doi:10.1109/cicc.1990.124764

Cited by 4 publications

(2 citation statements)

References 2 publications

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“…There are several ways how to choose the compressor function c(x) for compression law. Originally, in [12] and also in [8], compressor function c 0 :…”

Section: Scalar Quantizers and Companding Techniquementioning

confidence: 99%

“…It requires a very complex realization structure and also is time consuming. Hardware implementations of popular compression algorithms such as the Huffman coding [11], Lempel-Ziv coding [12], binary arithmetic coding [13], and the Rice algorithm [14] have been reported in the literature. A 12-bit A/D with a simplified Huffman encoder is presented in [15].…”

Section: Introductionmentioning

confidence: 99%

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Optimisation of variable-length code for data compression of memoryless Laplacian source

2011

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In this paper we present the efficient technique for compression and coding of memoryless Laplacian sources, which uses variable-length code (V LC). That technique is based on combination of two companding quantizers in the first case, and three companding quantizers in the second case. These quantizers have disjoint support regions, different number of representation levels and different compressor functions. The closed-form expressions are obtained for the distortion, average bit rate and signal to quantization noise ratio (SQN R). Presented numerical results point out the effects of rate-distortion (R-D) optimization on the system performances. Since our model assumes the general case of Laplacian distribution, it has a wide applications like coding of speech and images. It is shown that the difference of SQN R of our model and classical

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“…There are several ways how to choose the compressor function c(x) for compression law. Originally, in [12] and also in [8], compressor function c 0 :…”

Section: Scalar Quantizers and Companding Techniquementioning

confidence: 99%