{"title":"一种基于熵最大化的灰度图像阈值和量化快速算法","authors":"R. Benzid, D. Arar, M. Bentoumi","doi":"10.1109/SSD.2008.4632831","DOIUrl":null,"url":null,"abstract":"Presented is a fast technique dedicated to the multilevel image thresholding and quantization based on the Shannonpsilas entropy maximization. The elaborated method uses efficiently the cumulative density function for the rapid determination of the optimal thresholds for segmentation. Some simulation results are reported for the aim of illustration and demonstration of its effectiveness.","PeriodicalId":267264,"journal":{"name":"2008 5th International Multi-Conference on Systems, Signals and Devices","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"A fast technique for gray level image thresholding and quantization based on the entropy maximization\",\"authors\":\"R. Benzid, D. Arar, M. Bentoumi\",\"doi\":\"10.1109/SSD.2008.4632831\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Presented is a fast technique dedicated to the multilevel image thresholding and quantization based on the Shannonpsilas entropy maximization. The elaborated method uses efficiently the cumulative density function for the rapid determination of the optimal thresholds for segmentation. Some simulation results are reported for the aim of illustration and demonstration of its effectiveness.\",\"PeriodicalId\":267264,\"journal\":{\"name\":\"2008 5th International Multi-Conference on Systems, Signals and Devices\",\"volume\":\"71 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-07-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 5th International Multi-Conference on Systems, Signals and Devices\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSD.2008.4632831\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 5th International Multi-Conference on Systems, Signals and Devices","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSD.2008.4632831","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A fast technique for gray level image thresholding and quantization based on the entropy maximization
Presented is a fast technique dedicated to the multilevel image thresholding and quantization based on the Shannonpsilas entropy maximization. The elaborated method uses efficiently the cumulative density function for the rapid determination of the optimal thresholds for segmentation. Some simulation results are reported for the aim of illustration and demonstration of its effectiveness.
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