{"title":"基于复扩散方程的图像滤波方法","authors":"Lai Lianyou, X. Weijian","doi":"10.1109/ICICE.2017.8478930","DOIUrl":null,"url":null,"abstract":"The edges of an image filtered are blurred usually. An image filtering method using complex diffusion equation is proposed for solving this problem. The complex diffusion equation has real and imaginary parts which have different effects on images. Firstly, the image is filtered by the real part of the complex diffusion equation. Then, the edges of the image are detected by the imaginary part of the complex diffusion equation. Finally, the edges of the filtered image are restored by using the edges detected to generate the final filtered image. Experimental results show that the method proposed in this paper can better preserve the image edges features and has higher peak signal-to-noise ratio for the image filtered.","PeriodicalId":233396,"journal":{"name":"2017 International Conference on Information, Communication and Engineering (ICICE)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Image Filtering Method Using Complex Diffusion Equation\",\"authors\":\"Lai Lianyou, X. Weijian\",\"doi\":\"10.1109/ICICE.2017.8478930\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The edges of an image filtered are blurred usually. An image filtering method using complex diffusion equation is proposed for solving this problem. The complex diffusion equation has real and imaginary parts which have different effects on images. Firstly, the image is filtered by the real part of the complex diffusion equation. Then, the edges of the image are detected by the imaginary part of the complex diffusion equation. Finally, the edges of the filtered image are restored by using the edges detected to generate the final filtered image. Experimental results show that the method proposed in this paper can better preserve the image edges features and has higher peak signal-to-noise ratio for the image filtered.\",\"PeriodicalId\":233396,\"journal\":{\"name\":\"2017 International Conference on Information, Communication and Engineering (ICICE)\",\"volume\":\"72 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Information, Communication and Engineering (ICICE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICE.2017.8478930\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Information, Communication and Engineering (ICICE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICE.2017.8478930","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image Filtering Method Using Complex Diffusion Equation
The edges of an image filtered are blurred usually. An image filtering method using complex diffusion equation is proposed for solving this problem. The complex diffusion equation has real and imaginary parts which have different effects on images. Firstly, the image is filtered by the real part of the complex diffusion equation. Then, the edges of the image are detected by the imaginary part of the complex diffusion equation. Finally, the edges of the filtered image are restored by using the edges detected to generate the final filtered image. Experimental results show that the method proposed in this paper can better preserve the image edges features and has higher peak signal-to-noise ratio for the image filtered.