{"title":"基于细胞神经网络的渐进式图像重建","authors":"S. Itakura, Y. Tanji, T. Otake, Mamoru Tanaka","doi":"10.1109/ISCAS.2002.1009820","DOIUrl":null,"url":null,"abstract":"The progressive image reconstruction via CNN is presented, where the CNN template mapping an image to a domain concerned with the coefficients of the radial basis function network for image interpolation is provided. The analog CNN dynamics achieves massively parallel computing, thus, the proposed procedure would create a new paradigm of CNN at the point of very high-speed image decoding and encoding. The simulation results shows good performance of the proposed CNN for image reconstruction.","PeriodicalId":203750,"journal":{"name":"2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Progressive image reconstruction via cellular neural networks\",\"authors\":\"S. Itakura, Y. Tanji, T. Otake, Mamoru Tanaka\",\"doi\":\"10.1109/ISCAS.2002.1009820\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The progressive image reconstruction via CNN is presented, where the CNN template mapping an image to a domain concerned with the coefficients of the radial basis function network for image interpolation is provided. The analog CNN dynamics achieves massively parallel computing, thus, the proposed procedure would create a new paradigm of CNN at the point of very high-speed image decoding and encoding. The simulation results shows good performance of the proposed CNN for image reconstruction.\",\"PeriodicalId\":203750,\"journal\":{\"name\":\"2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCAS.2002.1009820\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCAS.2002.1009820","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Progressive image reconstruction via cellular neural networks
The progressive image reconstruction via CNN is presented, where the CNN template mapping an image to a domain concerned with the coefficients of the radial basis function network for image interpolation is provided. The analog CNN dynamics achieves massively parallel computing, thus, the proposed procedure would create a new paradigm of CNN at the point of very high-speed image decoding and encoding. The simulation results shows good performance of the proposed CNN for image reconstruction.