Fast algorithm for vector quantization in radiological image compression
| Autor: | Rémy Prost, Robert Goutte, Nabil M. Akrout |
|---|---|
| Rok vydání: | 1993 |
| Předmět: |
Linde–Buzo–Gray algorithm
Theoretical computer science Quantization (signal processing) ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Vector quantization Codebook Fast algorithm ComputingMethodologies_PATTERNRECOGNITION Computer Science::Computer Vision and Pattern Recognition U-matrix Cluster analysis Algorithm Computer Science::Information Theory Mathematics Image compression |
| Zdroj: | SPIE Proceedings. |
| ISSN: | 0277-786X |
| DOI: | 10.1117/12.146973 |
| Popis: | In Vector Quantization, the codebook generation requires a clustering scheme, where the number of the clusters (the codebook size) is pre-defined. There are several algorithms which resolve this problem. For example, we quote the well known Linde-Buzo-Gray (LBG) algorithm, and the recent finite state algorithm. Most of them are iterative, and thus, time consuming. Our purpose is to look for a fast one, which is necessary non-iterative and represents adequately the image to be coded. After a review of existing algorithms for codebook generation, we propose a Modified Decision-Directed Clustering (MDDC) technique for codebook generation and its application in radiological image. The Convergence of the (MDDC) algorithm to a globally sub-optimal codebook in finite time is proved. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|