Discrete minimum entropy quantization
We present a simple lower bound on the entropy of a quantized signal and a method for determining the minimum entropy quantization, subject to a maximum distortion, for a discrete memoryless random process. This quantization allows more efficient use of variable-order models for compression of image...
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| Veröffentlicht in: | IEEE transactions on image processing 1995-09, Vol.4 (9), p.1314-1317 |
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| container_end_page | 1317 |
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| container_issue | 9 |
| container_start_page | 1314 |
| container_title | IEEE transactions on image processing |
| container_volume | 4 |
| creator | Gormish, M.J. Gill, J.T. |
| description | We present a simple lower bound on the entropy of a quantized signal and a method for determining the minimum entropy quantization, subject to a maximum distortion, for a discrete memoryless random process. This quantization allows more efficient use of variable-order models for compression of images and sound.< > |
| doi_str_mv | 10.1109/83.413176 |
| format | Article |
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| identifier | ISSN: 1057-7149 |
| ispartof | IEEE transactions on image processing, 1995-09, Vol.4 (9), p.1314-1317 |
| issn | 1057-7149 1941-0042 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_27355534 |
| source | IEEE Electronic Library (IEL) |
| subjects | Annealing Application software Applied sciences Distortion measurement Entropy Exact sciences and technology Image classification Information, signal and communications theory Labeling Quantization Relaxation methods Sampling, quantization Signal and communications theory Telecommunications and information theory Testing Viterbi algorithm |
| title | Discrete minimum entropy quantization |
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