{"title":"面向压缩感知与重构的感知矩阵设计","authors":"H B Sharanabasaveshwara, Santosh M. Herur","doi":"10.1109/ICAECC.2018.8479466","DOIUrl":null,"url":null,"abstract":"The compressive sampling technique is an emerging sampling technique that reconstructs a sparse signal at sub-Nyquist rate. One of the concerns in compression sensing is design of sensing matrix. While random sensing matrix are widely in use, they have many disadvantages. In this paper a novel Deterministic Random Sensing Matrix is designed and tested on image of size 256 × 256. The result shows 24% improvement in reconstruction time over Random Sensing Matrix. Since the matrix is deterministic the storage requirement is less than the Random Sensing Matrix.","PeriodicalId":106991,"journal":{"name":"2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC)","volume":"352 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Designing of Sensing Matrix for Compressive Sensing and Reconstruction\",\"authors\":\"H B Sharanabasaveshwara, Santosh M. Herur\",\"doi\":\"10.1109/ICAECC.2018.8479466\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The compressive sampling technique is an emerging sampling technique that reconstructs a sparse signal at sub-Nyquist rate. One of the concerns in compression sensing is design of sensing matrix. While random sensing matrix are widely in use, they have many disadvantages. In this paper a novel Deterministic Random Sensing Matrix is designed and tested on image of size 256 × 256. The result shows 24% improvement in reconstruction time over Random Sensing Matrix. Since the matrix is deterministic the storage requirement is less than the Random Sensing Matrix.\",\"PeriodicalId\":106991,\"journal\":{\"name\":\"2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC)\",\"volume\":\"352 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAECC.2018.8479466\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAECC.2018.8479466","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Designing of Sensing Matrix for Compressive Sensing and Reconstruction
The compressive sampling technique is an emerging sampling technique that reconstructs a sparse signal at sub-Nyquist rate. One of the concerns in compression sensing is design of sensing matrix. While random sensing matrix are widely in use, they have many disadvantages. In this paper a novel Deterministic Random Sensing Matrix is designed and tested on image of size 256 × 256. The result shows 24% improvement in reconstruction time over Random Sensing Matrix. Since the matrix is deterministic the storage requirement is less than the Random Sensing Matrix.
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