{"title":"2D-discrete walsh wavelet transform for image compression with arithmetic coding","authors":"Sunil Malviya, N. Gupta, Vibhanshu Shirvastava","doi":"10.1109/ICCCNT.2013.6726772","DOIUrl":null,"url":null,"abstract":"With the increasing demand of storage and transmission of digital images, image compression is now become an essential applications for storage and transmission. This paper proposes a new scheme for image compression using DWT (Discrete Wavelet Transform) taking into account sub-band features in the frequency domains. Method involves two steps firstly a two levels discrete wavelet transforms on selected input image. The original image is decomposed at different 8×8 blocks, after that apply 2D-Walsh-Wavelet Transform (WWT) on each 8×8 block of the low frequency sub-band. Firstly dividing each sub-band by a factor and then apply Arithmetic Coding on each sub-band independently. Transform each 8×8 block from LL2, and then divide each block 8×8 separated into; DC value and compressed by Arithmetic coding.","PeriodicalId":6330,"journal":{"name":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","volume":"155 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCNT.2013.6726772","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
With the increasing demand of storage and transmission of digital images, image compression is now become an essential applications for storage and transmission. This paper proposes a new scheme for image compression using DWT (Discrete Wavelet Transform) taking into account sub-band features in the frequency domains. Method involves two steps firstly a two levels discrete wavelet transforms on selected input image. The original image is decomposed at different 8×8 blocks, after that apply 2D-Walsh-Wavelet Transform (WWT) on each 8×8 block of the low frequency sub-band. Firstly dividing each sub-band by a factor and then apply Arithmetic Coding on each sub-band independently. Transform each 8×8 block from LL2, and then divide each block 8×8 separated into; DC value and compressed by Arithmetic coding.