{"title":"图像的半因果递归滤波","authors":"Anilk . Jain","doi":"10.1109/CDC.1975.270651","DOIUrl":null,"url":null,"abstract":"A two dimensional discrete stochastic model for representing images is developed. This representation leads to a \"hybrid\" algorithm for spatial filtering of images. A \"hybrid\" algorithm is one where the filter equations are solved in a transform domain in one direction and in spatial domain in the other. Application of the model to linear filtering of images leads to scalar recursive filtering equations requiring only O(N2log2N) computations for N×N images. Examples on a 255 × 255 image are given.","PeriodicalId":164707,"journal":{"name":"1975 IEEE Conference on Decision and Control including the 14th Symposium on Adaptive Processes","volume":"25 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1975-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Semicausal recursive filtering of images\",\"authors\":\"Anilk . Jain\",\"doi\":\"10.1109/CDC.1975.270651\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A two dimensional discrete stochastic model for representing images is developed. This representation leads to a \\\"hybrid\\\" algorithm for spatial filtering of images. A \\\"hybrid\\\" algorithm is one where the filter equations are solved in a transform domain in one direction and in spatial domain in the other. Application of the model to linear filtering of images leads to scalar recursive filtering equations requiring only O(N2log2N) computations for N×N images. Examples on a 255 × 255 image are given.\",\"PeriodicalId\":164707,\"journal\":{\"name\":\"1975 IEEE Conference on Decision and Control including the 14th Symposium on Adaptive Processes\",\"volume\":\"25 3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1975-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1975 IEEE Conference on Decision and Control including the 14th Symposium on Adaptive Processes\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.1975.270651\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1975 IEEE Conference on Decision and Control including the 14th Symposium on Adaptive Processes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.1975.270651","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A two dimensional discrete stochastic model for representing images is developed. This representation leads to a "hybrid" algorithm for spatial filtering of images. A "hybrid" algorithm is one where the filter equations are solved in a transform domain in one direction and in spatial domain in the other. Application of the model to linear filtering of images leads to scalar recursive filtering equations requiring only O(N2log2N) computations for N×N images. Examples on a 255 × 255 image are given.
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