{"title":"利用改进的吠陀乘法器进行三级二维离散小波变换","authors":"S. Tripathi, Bharat Mishra","doi":"10.1109/CSNT.2017.8418535","DOIUrl":null,"url":null,"abstract":"The various 1-D and 2-D DWT architectures that exist in the literature are Row-column, parallel filter, folded, flipping and recursive structures. The architectures vary with respect to the computational and hardware requirement, the memory required to store the input image, and the intermediate coefficients. The main objective of this research work is to derive efficient VLSI architectures, for the hardware implementation of the DWT, using Vedic multiplier and improving the hardware complexities and speed of existing architectures.","PeriodicalId":382417,"journal":{"name":"2017 7th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Three stage 2-D discrete wavelet transform using modified vedic multiplier\",\"authors\":\"S. Tripathi, Bharat Mishra\",\"doi\":\"10.1109/CSNT.2017.8418535\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The various 1-D and 2-D DWT architectures that exist in the literature are Row-column, parallel filter, folded, flipping and recursive structures. The architectures vary with respect to the computational and hardware requirement, the memory required to store the input image, and the intermediate coefficients. The main objective of this research work is to derive efficient VLSI architectures, for the hardware implementation of the DWT, using Vedic multiplier and improving the hardware complexities and speed of existing architectures.\",\"PeriodicalId\":382417,\"journal\":{\"name\":\"2017 7th International Conference on Communication Systems and Network Technologies (CSNT)\",\"volume\":\"151 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 7th International Conference on Communication Systems and Network Technologies (CSNT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSNT.2017.8418535\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 7th International Conference on Communication Systems and Network Technologies (CSNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSNT.2017.8418535","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Three stage 2-D discrete wavelet transform using modified vedic multiplier
The various 1-D and 2-D DWT architectures that exist in the literature are Row-column, parallel filter, folded, flipping and recursive structures. The architectures vary with respect to the computational and hardware requirement, the memory required to store the input image, and the intermediate coefficients. The main objective of this research work is to derive efficient VLSI architectures, for the hardware implementation of the DWT, using Vedic multiplier and improving the hardware complexities and speed of existing architectures.