{"title":"估计失焦模糊的数学模型","authors":"M. Moghaddam","doi":"10.1109/ISPA.2007.4383705","DOIUrl":null,"url":null,"abstract":"Blur identification is one of the most important parts of image restoration. The most conventional blur that occurs in images is out of focus, which is generated because of lens defocus. In this paper, a new method is presented to estimate out of focus blur parameters robustly. This method is based on mathematical modeling of zero crossing in log of Fourier spectrum. We have presented a formula to calculate out of focus blur parameters using circular hough transform and statistical measures. Experimental results show the error tolerance of the method is about 2% and this works on noisy images with SNR ges 55 dB, robustly.","PeriodicalId":112420,"journal":{"name":"2007 5th International Symposium on Image and Signal Processing and Analysis","volume":"12 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"36","resultStr":"{\"title\":\"A Mathematical Model to Estimate Out of Focus Blur\",\"authors\":\"M. Moghaddam\",\"doi\":\"10.1109/ISPA.2007.4383705\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Blur identification is one of the most important parts of image restoration. The most conventional blur that occurs in images is out of focus, which is generated because of lens defocus. In this paper, a new method is presented to estimate out of focus blur parameters robustly. This method is based on mathematical modeling of zero crossing in log of Fourier spectrum. We have presented a formula to calculate out of focus blur parameters using circular hough transform and statistical measures. Experimental results show the error tolerance of the method is about 2% and this works on noisy images with SNR ges 55 dB, robustly.\",\"PeriodicalId\":112420,\"journal\":{\"name\":\"2007 5th International Symposium on Image and Signal Processing and Analysis\",\"volume\":\"12 3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-11-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"36\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 5th International Symposium on Image and Signal Processing and Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPA.2007.4383705\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 5th International Symposium on Image and Signal Processing and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPA.2007.4383705","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Mathematical Model to Estimate Out of Focus Blur
Blur identification is one of the most important parts of image restoration. The most conventional blur that occurs in images is out of focus, which is generated because of lens defocus. In this paper, a new method is presented to estimate out of focus blur parameters robustly. This method is based on mathematical modeling of zero crossing in log of Fourier spectrum. We have presented a formula to calculate out of focus blur parameters using circular hough transform and statistical measures. Experimental results show the error tolerance of the method is about 2% and this works on noisy images with SNR ges 55 dB, robustly.