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

2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS) Pub Date : 2018-10-15 DOI:10.1109/ICSPCS.2018.8631781

Michaela Novosadová, P. Rajmic

{"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}

引用次数: 1

摘要

本文采用了一种包含稀疏性的过完备分段多项式图像模型。研究表明，利用该模型可以对图像中的边缘进行鲁棒化处理。所提出的方法的两个变体都被证明优于使用经典边缘检测核。该方法同样适用于图像分割。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

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.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)

自引率

0.00%

发文量