Gourav Kumar Javeriya, Deepak Gupta, Shikha Gupta, A. Dahiya
{"title":"图像各块上的噪声分布及其分析","authors":"Gourav Kumar Javeriya, Deepak Gupta, Shikha Gupta, A. Dahiya","doi":"10.1109/IC3I.2014.7019581","DOIUrl":null,"url":null,"abstract":"In this paper we work on noise analysis on blocks of images. We introduced a technique through which we are observing the effect of noise on various blocks of an image. Finally we are resultant the maximum and minimum effect of noise. For the proposed work we are considering only Gaussian noise. PSNR and SNR values are calculated for images with and without blocks. Proposed work has been implemented on many images of same format. This paper is highly beneficial for reducing the noise to only those blocks which are highly affected instead of applying the process of noise removal on whole image. This can reduce the processing time highly on the cost of small considerable noise. Also, the another advantage of this approach is that in the real time system, the blocks of image having high value of noise can be determined and can be processed further leaving the blocks with the low values of noise. This can effectively reduce the processing time without applying an extra effort.","PeriodicalId":430848,"journal":{"name":"2014 International Conference on Contemporary Computing and Informatics (IC3I)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Noise distribution on various blocks of image and their analysis\",\"authors\":\"Gourav Kumar Javeriya, Deepak Gupta, Shikha Gupta, A. Dahiya\",\"doi\":\"10.1109/IC3I.2014.7019581\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we work on noise analysis on blocks of images. We introduced a technique through which we are observing the effect of noise on various blocks of an image. Finally we are resultant the maximum and minimum effect of noise. For the proposed work we are considering only Gaussian noise. PSNR and SNR values are calculated for images with and without blocks. Proposed work has been implemented on many images of same format. This paper is highly beneficial for reducing the noise to only those blocks which are highly affected instead of applying the process of noise removal on whole image. This can reduce the processing time highly on the cost of small considerable noise. Also, the another advantage of this approach is that in the real time system, the blocks of image having high value of noise can be determined and can be processed further leaving the blocks with the low values of noise. This can effectively reduce the processing time without applying an extra effort.\",\"PeriodicalId\":430848,\"journal\":{\"name\":\"2014 International Conference on Contemporary Computing and Informatics (IC3I)\",\"volume\":\"103 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Contemporary Computing and Informatics (IC3I)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IC3I.2014.7019581\",\"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 International Conference on Contemporary Computing and Informatics (IC3I)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC3I.2014.7019581","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Noise distribution on various blocks of image and their analysis
In this paper we work on noise analysis on blocks of images. We introduced a technique through which we are observing the effect of noise on various blocks of an image. Finally we are resultant the maximum and minimum effect of noise. For the proposed work we are considering only Gaussian noise. PSNR and SNR values are calculated for images with and without blocks. Proposed work has been implemented on many images of same format. This paper is highly beneficial for reducing the noise to only those blocks which are highly affected instead of applying the process of noise removal on whole image. This can reduce the processing time highly on the cost of small considerable noise. Also, the another advantage of this approach is that in the real time system, the blocks of image having high value of noise can be determined and can be processed further leaving the blocks with the low values of noise. This can effectively reduce the processing time without applying an extra effort.