{"title":"Coding gain of intra/inter-frame subband systems","authors":"G. Galvagno, G. Mian, R. Rinaldo","doi":"10.1109/DCC.1995.515559","DOIUrl":null,"url":null,"abstract":"Summary form only given. Typical image sequence coders use motion compensation techniques in connection to coding of the motion compensated difference images (interframe coding). Moreover, the difference loop is initialized from time to time by intraframe coding of images. It is therefore important to have a procedure that allows to evaluate the performance of a particular coding scheme: coding gain and rate-distortion figures are used in this work to this purpose. We present an explicit procedure to compute the coding gain for two-dimensional separable subband systems, both in the case of a uniform and a pyramid subband decomposition, and for the case of interframe coding. The technique operates in the signal domain and requires the knowledge of the autocorrelation function of the input process. In the case of a separable subband system and image spectrum, the coding gain can be computed by combining the results relative to appropriately defined one-dimensional filtering schemes, thus making the technique very attractive in terms of computational complexity. We consider both the case of a uniform subband decomposition and of a pyramid decomposition. The developed procedure is applied to compute the subband coding gain for motion compensated signals in the case of images modeled as separable Markov processes: different filter banks are compared to each other and to transform coding. In order to have indications on the effectiveness of motion compensation, we also compute the coding gain for intraframe images. We show that the results for the image models are in very good agreement with those obtained with real-world data.","PeriodicalId":107017,"journal":{"name":"Proceedings DCC '95 Data Compression Conference","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings DCC '95 Data Compression Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCC.1995.515559","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Summary form only given. Typical image sequence coders use motion compensation techniques in connection to coding of the motion compensated difference images (interframe coding). Moreover, the difference loop is initialized from time to time by intraframe coding of images. It is therefore important to have a procedure that allows to evaluate the performance of a particular coding scheme: coding gain and rate-distortion figures are used in this work to this purpose. We present an explicit procedure to compute the coding gain for two-dimensional separable subband systems, both in the case of a uniform and a pyramid subband decomposition, and for the case of interframe coding. The technique operates in the signal domain and requires the knowledge of the autocorrelation function of the input process. In the case of a separable subband system and image spectrum, the coding gain can be computed by combining the results relative to appropriately defined one-dimensional filtering schemes, thus making the technique very attractive in terms of computational complexity. We consider both the case of a uniform subband decomposition and of a pyramid decomposition. The developed procedure is applied to compute the subband coding gain for motion compensated signals in the case of images modeled as separable Markov processes: different filter banks are compared to each other and to transform coding. In order to have indications on the effectiveness of motion compensation, we also compute the coding gain for intraframe images. We show that the results for the image models are in very good agreement with those obtained with real-world data.