{"title":"Image edge block classification for CVQ using the SD filter","authors":"J. Farison, M. Quweider","doi":"10.1109/ICASSP.1995.480057","DOIUrl":null,"url":null,"abstract":"A novel technique to classify image edge blocks is presented. It is based on defining a set of linearly independent signature vectors with a one to one association with the edge classes. A set of filter vectors emphasizing the projection of one signature vector and suppressing all others is then designed. Classification of an input edge block is accomplished by choosing the index of the filter with the maximum output magnitude. Coded images based on this classification are shown to preserve their quality and enjoy considerable dB gain over two existing methods. The new technique can be easily implemented using a parallel algorithm with little storage requirement.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"1995 International Conference on Acoustics, Speech, and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.1995.480057","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
A novel technique to classify image edge blocks is presented. It is based on defining a set of linearly independent signature vectors with a one to one association with the edge classes. A set of filter vectors emphasizing the projection of one signature vector and suppressing all others is then designed. Classification of an input edge block is accomplished by choosing the index of the filter with the maximum output magnitude. Coded images based on this classification are shown to preserve their quality and enjoy considerable dB gain over two existing methods. The new technique can be easily implemented using a parallel algorithm with little storage requirement.