{"title":"二维离散沃尔什小波变换图像压缩与算术编码","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":"{\"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}","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}
2D-discrete walsh wavelet transform for image compression with arithmetic coding
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.