{"title":"Orthogonal polynomials based low bit rate image coding","authors":"T. Karthikeyan, R. Krishnamoorthy, B. Praburaj","doi":"10.1109/MVIP.2012.6428764","DOIUrl":null,"url":null,"abstract":"In this paper, a new and efficient method for transform coding of 2-D monochrome images based on orthogonal polynomials has been proposed. The proposed orthogonal polynomials based transform coding system has the encoder, consisting of a polynomial transform operation followed by quantization of transform coefficients and the entropy coding of quantized coefficients. After the encoded bit stream of an input image is transmitted over the channel, the decoder reverses all the functionalities applied in the encoder and tries to reconstruct a decoded image that looks as close as possible to the original input image. The result of the proposed coding are compared with the DCT scheme. The new coding algorithm results in a considerable reduction in computation time and provides better reconstructed picture quality.","PeriodicalId":170271,"journal":{"name":"2012 International Conference on Machine Vision and Image Processing (MVIP)","volume":"263 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Machine Vision and Image Processing (MVIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MVIP.2012.6428764","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
In this paper, a new and efficient method for transform coding of 2-D monochrome images based on orthogonal polynomials has been proposed. The proposed orthogonal polynomials based transform coding system has the encoder, consisting of a polynomial transform operation followed by quantization of transform coefficients and the entropy coding of quantized coefficients. After the encoded bit stream of an input image is transmitted over the channel, the decoder reverses all the functionalities applied in the encoder and tries to reconstruct a decoded image that looks as close as possible to the original input image. The result of the proposed coding are compared with the DCT scheme. The new coding algorithm results in a considerable reduction in computation time and provides better reconstructed picture quality.