{"title":"二维阈值的快速递归算法","authors":"Gong Jian, Liang Liyuan, Chen Weinan","doi":"10.1109/ICSIGP.1996.566327","DOIUrl":null,"url":null,"abstract":"Two-dimensional (2D) thresholding behaves well in segmenting images of low signal-to-noise ratio. But the computational complexity of the conventional 2D entropic algorithm is bounded by O(L/sup 4/). Firstly, a fast recursive 2D entropic thresholding algorithm is proposed. By rewriting the formula for calculation of the entropy in a recurrence form, a great deal of calculation is saved. Analysis shows that the computational complexity of 2D entropic thresholding is reduced to O(L/sup 2/). The fast recursive algorithm is also used successfully in the 2D Otsu (1979) method. Experimental results show that the processing time of each image is reduced from more than 2 h to less than 10 sec. The required memory space is also greatly reduced.","PeriodicalId":385432,"journal":{"name":"Proceedings of Third International Conference on Signal Processing (ICSP'96)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"A fast recursive algorithm for two-dimensional thresholding\",\"authors\":\"Gong Jian, Liang Liyuan, Chen Weinan\",\"doi\":\"10.1109/ICSIGP.1996.566327\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Two-dimensional (2D) thresholding behaves well in segmenting images of low signal-to-noise ratio. But the computational complexity of the conventional 2D entropic algorithm is bounded by O(L/sup 4/). Firstly, a fast recursive 2D entropic thresholding algorithm is proposed. By rewriting the formula for calculation of the entropy in a recurrence form, a great deal of calculation is saved. Analysis shows that the computational complexity of 2D entropic thresholding is reduced to O(L/sup 2/). The fast recursive algorithm is also used successfully in the 2D Otsu (1979) method. Experimental results show that the processing time of each image is reduced from more than 2 h to less than 10 sec. The required memory space is also greatly reduced.\",\"PeriodicalId\":385432,\"journal\":{\"name\":\"Proceedings of Third International Conference on Signal Processing (ICSP'96)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of Third International Conference on Signal Processing (ICSP'96)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSIGP.1996.566327\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of Third International Conference on Signal Processing (ICSP'96)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSIGP.1996.566327","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A fast recursive algorithm for two-dimensional thresholding
Two-dimensional (2D) thresholding behaves well in segmenting images of low signal-to-noise ratio. But the computational complexity of the conventional 2D entropic algorithm is bounded by O(L/sup 4/). Firstly, a fast recursive 2D entropic thresholding algorithm is proposed. By rewriting the formula for calculation of the entropy in a recurrence form, a great deal of calculation is saved. Analysis shows that the computational complexity of 2D entropic thresholding is reduced to O(L/sup 2/). The fast recursive algorithm is also used successfully in the 2D Otsu (1979) method. Experimental results show that the processing time of each image is reduced from more than 2 h to less than 10 sec. The required memory space is also greatly reduced.