Ayush Kumar, Nimisha Agarwal, Juhi Bhadviya, G. Mittal, G. Ramponi
{"title":"一种有效的去除椒盐噪声的边缘保持新技术","authors":"Ayush Kumar, Nimisha Agarwal, Juhi Bhadviya, G. Mittal, G. Ramponi","doi":"10.1109/ISPA.2013.6703707","DOIUrl":null,"url":null,"abstract":"This paper proposes an efficient procedure for removal of salt and pepper noises from the noisy images on the basis of their local edge preserving filters. This algorithm consists of two major stages. In the first stage, the maximum and minimum pixel value in the the corrupted image is used to select noisy pixels or noise free pixels and then in second stage, local edge preserving filters are used on the basis of noisy pixel detected and the nature of its neighboring pixels in the selected window. Comparing the obtained results with other computationally simple noise removal techniques, our proposed algorithm gives much better qualitative and quantitative performance. Due to its simplicity and low computational cost, our method is suitable for its application in many real time situations.","PeriodicalId":425029,"journal":{"name":"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"An efficient new edge preserving technique for removal of salt and pepper noise\",\"authors\":\"Ayush Kumar, Nimisha Agarwal, Juhi Bhadviya, G. Mittal, G. Ramponi\",\"doi\":\"10.1109/ISPA.2013.6703707\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes an efficient procedure for removal of salt and pepper noises from the noisy images on the basis of their local edge preserving filters. This algorithm consists of two major stages. In the first stage, the maximum and minimum pixel value in the the corrupted image is used to select noisy pixels or noise free pixels and then in second stage, local edge preserving filters are used on the basis of noisy pixel detected and the nature of its neighboring pixels in the selected window. Comparing the obtained results with other computationally simple noise removal techniques, our proposed algorithm gives much better qualitative and quantitative performance. Due to its simplicity and low computational cost, our method is suitable for its application in many real time situations.\",\"PeriodicalId\":425029,\"journal\":{\"name\":\"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPA.2013.6703707\",\"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 8th International Symposium on Image and Signal Processing and Analysis (ISPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPA.2013.6703707","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An efficient new edge preserving technique for removal of salt and pepper noise
This paper proposes an efficient procedure for removal of salt and pepper noises from the noisy images on the basis of their local edge preserving filters. This algorithm consists of two major stages. In the first stage, the maximum and minimum pixel value in the the corrupted image is used to select noisy pixels or noise free pixels and then in second stage, local edge preserving filters are used on the basis of noisy pixel detected and the nature of its neighboring pixels in the selected window. Comparing the obtained results with other computationally simple noise removal techniques, our proposed algorithm gives much better qualitative and quantitative performance. Due to its simplicity and low computational cost, our method is suitable for its application in many real time situations.