{"title":"基于一维离散小波信噪分离的图像边缘检测算法","authors":"X. Li, X. Zhao","doi":"10.1109/GCIS.2012.10","DOIUrl":null,"url":null,"abstract":"By using wavelet transform modulus maxima method to detection image edge, edge details are easily smoothed out in the large scale analysis and related parameters great influenced by the noise is not easy to extract in traditional small scale analysis. To solve this problem, this paper proposes a method based on one-dimensional discrete wavelet image edge detection. This algorithm decompose image into one-dimensional signal, making signal-noise separation with one-dimensional discrete wavelet, and detect the edge of de-noised signal's high frequency components. The article has experimented the multiple vehicle detection in real scene for many times, and the result shows that this algorithm solved the problem that exist in wavelet transform modulus maxima method to test image edges in small scale analysis, restraining noise better, and had higher precision in edge localization.","PeriodicalId":337629,"journal":{"name":"2012 Third Global Congress on Intelligent Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Image Edge Detection Algorithm Based on One-Dimensional Discrete Wavelet Signal-Noise Separation\",\"authors\":\"X. Li, X. Zhao\",\"doi\":\"10.1109/GCIS.2012.10\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"By using wavelet transform modulus maxima method to detection image edge, edge details are easily smoothed out in the large scale analysis and related parameters great influenced by the noise is not easy to extract in traditional small scale analysis. To solve this problem, this paper proposes a method based on one-dimensional discrete wavelet image edge detection. This algorithm decompose image into one-dimensional signal, making signal-noise separation with one-dimensional discrete wavelet, and detect the edge of de-noised signal's high frequency components. The article has experimented the multiple vehicle detection in real scene for many times, and the result shows that this algorithm solved the problem that exist in wavelet transform modulus maxima method to test image edges in small scale analysis, restraining noise better, and had higher precision in edge localization.\",\"PeriodicalId\":337629,\"journal\":{\"name\":\"2012 Third Global Congress on Intelligent Systems\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Third Global Congress on Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GCIS.2012.10\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Third Global Congress on Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GCIS.2012.10","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Image Edge Detection Algorithm Based on One-Dimensional Discrete Wavelet Signal-Noise Separation
By using wavelet transform modulus maxima method to detection image edge, edge details are easily smoothed out in the large scale analysis and related parameters great influenced by the noise is not easy to extract in traditional small scale analysis. To solve this problem, this paper proposes a method based on one-dimensional discrete wavelet image edge detection. This algorithm decompose image into one-dimensional signal, making signal-noise separation with one-dimensional discrete wavelet, and detect the edge of de-noised signal's high frequency components. The article has experimented the multiple vehicle detection in real scene for many times, and the result shows that this algorithm solved the problem that exist in wavelet transform modulus maxima method to test image edges in small scale analysis, restraining noise better, and had higher precision in edge localization.