{"title":"训练用于椒盐噪声滤波的元胞自动机","authors":"A. P. Shukla, S. Agarwal","doi":"10.1109/CIPECH.2014.7019128","DOIUrl":null,"url":null,"abstract":"Cellular Automata is significantly applying to image processing operations. The description about the use of training of cellular automata for filtering the salt and pepper noise in binary images is exemplified in this paper. The selection of the best rule set from large search space has been performed on the basis of sequential floating forward search method. The peak signal to noise ratio values between original and filtered image is used as the objective function. The proposed method is also compared with some standard methods and found to perform better in respect to restoration of the image.","PeriodicalId":170027,"journal":{"name":"2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH)","volume":"68-69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Training cellular automata for salt and pepper noise filtering\",\"authors\":\"A. P. Shukla, S. Agarwal\",\"doi\":\"10.1109/CIPECH.2014.7019128\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cellular Automata is significantly applying to image processing operations. The description about the use of training of cellular automata for filtering the salt and pepper noise in binary images is exemplified in this paper. The selection of the best rule set from large search space has been performed on the basis of sequential floating forward search method. The peak signal to noise ratio values between original and filtered image is used as the objective function. The proposed method is also compared with some standard methods and found to perform better in respect to restoration of the image.\",\"PeriodicalId\":170027,\"journal\":{\"name\":\"2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH)\",\"volume\":\"68-69 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIPECH.2014.7019128\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIPECH.2014.7019128","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Training cellular automata for salt and pepper noise filtering
Cellular Automata is significantly applying to image processing operations. The description about the use of training of cellular automata for filtering the salt and pepper noise in binary images is exemplified in this paper. The selection of the best rule set from large search space has been performed on the basis of sequential floating forward search method. The peak signal to noise ratio values between original and filtered image is used as the objective function. The proposed method is also compared with some standard methods and found to perform better in respect to restoration of the image.