{"title":"边缘自适应滤波:多少和哪个方向?","authors":"R. Jha, M. Jernigan","doi":"10.1109/ICSMC.1989.71318","DOIUrl":null,"url":null,"abstract":"A novel adaptive filter for edge-preserving smoothing of noisy images is introduced. The novelty of the filter is that its region of support is tuned simultaneously in its size and orientation. An edge strength measure is extracted from the local variance and used to control the size of the window. The gradient direction is used to adapt the orientation of the window. The use of both edge strength and edge detection information allows large windows to be used even in the vicinity of edges. The filter has been tested for additive white Gaussian noise with the mean as the point estimator over local windows, and for additive white impulse noise with the median as the point estimator. Results, particularly for the adaptive median filter, are very promising. The results show that the filter does greater smoothing in the vicinity of edges without compromising performance away from edges and the edge structure of the image.<<ETX>>","PeriodicalId":72691,"journal":{"name":"Conference proceedings. IEEE International Conference on Systems, Man, and Cybernetics","volume":"73 1","pages":"364-366 vol.1"},"PeriodicalIF":0.0000,"publicationDate":"1989-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Edge adaptive filtering: how much and which direction?\",\"authors\":\"R. Jha, M. Jernigan\",\"doi\":\"10.1109/ICSMC.1989.71318\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A novel adaptive filter for edge-preserving smoothing of noisy images is introduced. The novelty of the filter is that its region of support is tuned simultaneously in its size and orientation. An edge strength measure is extracted from the local variance and used to control the size of the window. The gradient direction is used to adapt the orientation of the window. The use of both edge strength and edge detection information allows large windows to be used even in the vicinity of edges. The filter has been tested for additive white Gaussian noise with the mean as the point estimator over local windows, and for additive white impulse noise with the median as the point estimator. Results, particularly for the adaptive median filter, are very promising. The results show that the filter does greater smoothing in the vicinity of edges without compromising performance away from edges and the edge structure of the image.<<ETX>>\",\"PeriodicalId\":72691,\"journal\":{\"name\":\"Conference proceedings. IEEE International Conference on Systems, Man, and Cybernetics\",\"volume\":\"73 1\",\"pages\":\"364-366 vol.1\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1989-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Conference proceedings. IEEE International Conference on Systems, Man, and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSMC.1989.71318\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference proceedings. IEEE International Conference on Systems, Man, and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSMC.1989.71318","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Edge adaptive filtering: how much and which direction?
A novel adaptive filter for edge-preserving smoothing of noisy images is introduced. The novelty of the filter is that its region of support is tuned simultaneously in its size and orientation. An edge strength measure is extracted from the local variance and used to control the size of the window. The gradient direction is used to adapt the orientation of the window. The use of both edge strength and edge detection information allows large windows to be used even in the vicinity of edges. The filter has been tested for additive white Gaussian noise with the mean as the point estimator over local windows, and for additive white impulse noise with the median as the point estimator. Results, particularly for the adaptive median filter, are very promising. The results show that the filter does greater smoothing in the vicinity of edges without compromising performance away from edges and the edge structure of the image.<>