{"title":"结合随机匹配滤波器和<s:1>特罗斯算法进行SAS图像去噪","authors":"F. Chaillan, P. Courmontagne","doi":"10.1109/OCEANSAP.2006.4393855","DOIUrl":null,"url":null,"abstract":"The wide research domain concerning SAS image de-noising shows the complexity of the problem. SAS devices designed to explore underwater world generate noise-corrupted data, strongly disturbed by the speckle noise, which affect both radiometric and spatial resolutions. Although many de-noising filtering techniques exist in the signal processing society and have shown their efficiency, they suffer of an important restrictive problem: the spatial resolution degradation. The matter is to design a processing having a strong de-noising power while preserving the spatial resolution. To perform this task, we present in this study a new way of SAS image de-noising consisting in coupling an efficient filtering technique, the stochastic matched filtering method, with a multi-resolution analysis technique, the a Trous algorithm. Comparison with some classical approaches on real SAS data reveal the efficiency of such an idea.","PeriodicalId":268341,"journal":{"name":"OCEANS 2006 - Asia Pacific","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Coupling the stochastic matched filter and the à Trous algorithm for SAS image de-noising\",\"authors\":\"F. Chaillan, P. Courmontagne\",\"doi\":\"10.1109/OCEANSAP.2006.4393855\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The wide research domain concerning SAS image de-noising shows the complexity of the problem. SAS devices designed to explore underwater world generate noise-corrupted data, strongly disturbed by the speckle noise, which affect both radiometric and spatial resolutions. Although many de-noising filtering techniques exist in the signal processing society and have shown their efficiency, they suffer of an important restrictive problem: the spatial resolution degradation. The matter is to design a processing having a strong de-noising power while preserving the spatial resolution. To perform this task, we present in this study a new way of SAS image de-noising consisting in coupling an efficient filtering technique, the stochastic matched filtering method, with a multi-resolution analysis technique, the a Trous algorithm. Comparison with some classical approaches on real SAS data reveal the efficiency of such an idea.\",\"PeriodicalId\":268341,\"journal\":{\"name\":\"OCEANS 2006 - Asia Pacific\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"OCEANS 2006 - Asia Pacific\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/OCEANSAP.2006.4393855\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"OCEANS 2006 - Asia Pacific","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/OCEANSAP.2006.4393855","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Coupling the stochastic matched filter and the à Trous algorithm for SAS image de-noising
The wide research domain concerning SAS image de-noising shows the complexity of the problem. SAS devices designed to explore underwater world generate noise-corrupted data, strongly disturbed by the speckle noise, which affect both radiometric and spatial resolutions. Although many de-noising filtering techniques exist in the signal processing society and have shown their efficiency, they suffer of an important restrictive problem: the spatial resolution degradation. The matter is to design a processing having a strong de-noising power while preserving the spatial resolution. To perform this task, we present in this study a new way of SAS image de-noising consisting in coupling an efficient filtering technique, the stochastic matched filtering method, with a multi-resolution analysis technique, the a Trous algorithm. Comparison with some classical approaches on real SAS data reveal the efficiency of such an idea.