{"title":"采用过完备分段多项式模型对图像边缘进行了较好的分解","authors":"Michaela Novosadová, P. Rajmic","doi":"10.1109/ICSPCS.2018.8631781","DOIUrl":null,"url":null,"abstract":"Used in the paper is an overcomplete piecewise-polynomial image model incorporating sparsity. The paper shows that using such a model, the edges in the image can be resolved robustly with respect to noise. Two variants of the proposed approach are both shown to be superior to the use of the classic edge detecting kernels. The proposed method is in turn also suitable for image segmentation.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Image Edges Resolved Well When Using an Overcomplete Piecewise-Polynomial Model\",\"authors\":\"Michaela Novosadová, P. Rajmic\",\"doi\":\"10.1109/ICSPCS.2018.8631781\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Used in the paper is an overcomplete piecewise-polynomial image model incorporating sparsity. The paper shows that using such a model, the edges in the image can be resolved robustly with respect to noise. Two variants of the proposed approach are both shown to be superior to the use of the classic edge detecting kernels. The proposed method is in turn also suitable for image segmentation.\",\"PeriodicalId\":179948,\"journal\":{\"name\":\"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSPCS.2018.8631781\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSPCS.2018.8631781","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image Edges Resolved Well When Using an Overcomplete Piecewise-Polynomial Model
Used in the paper is an overcomplete piecewise-polynomial image model incorporating sparsity. The paper shows that using such a model, the edges in the image can be resolved robustly with respect to noise. Two variants of the proposed approach are both shown to be superior to the use of the classic edge detecting kernels. The proposed method is in turn also suitable for image segmentation.
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