M. Bóo, Francisco Argüello, J. Bruguera, E. Zapata
{"title":"High performance VLSI architecture for the trellis coded quantization","authors":"M. Bóo, Francisco Argüello, J. Bruguera, E. Zapata","doi":"10.1109/ICIP.1996.561073","DOIUrl":null,"url":null,"abstract":"Trellis coded quantization (TCQ) is an efficient technique for encoding memoryless sources. Furthermore TCQ can be incorporated into a transform coding structure (such as the discrete cosine transform) for encoding monochrome and color images with fixed rate or entropy-constrained schemes. In all these cases an expanded codebook is partitioned into subsets used to label the branches of an appropriate graph (trellis). For a given data sequence, the Viterbi algorithm is then used to find the minimum mean square error path through the trellis. We present a generic architecture scheme that can be easily adapted to the different TCQ image compression methods. We also present a formal model that permits a regular and modular design solution that is optimal for a particular set of area and/or speed constraints.","PeriodicalId":192947,"journal":{"name":"Proceedings of 3rd IEEE International Conference on Image Processing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 3rd IEEE International Conference on Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.1996.561073","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Trellis coded quantization (TCQ) is an efficient technique for encoding memoryless sources. Furthermore TCQ can be incorporated into a transform coding structure (such as the discrete cosine transform) for encoding monochrome and color images with fixed rate or entropy-constrained schemes. In all these cases an expanded codebook is partitioned into subsets used to label the branches of an appropriate graph (trellis). For a given data sequence, the Viterbi algorithm is then used to find the minimum mean square error path through the trellis. We present a generic architecture scheme that can be easily adapted to the different TCQ image compression methods. We also present a formal model that permits a regular and modular design solution that is optimal for a particular set of area and/or speed constraints.