{"title":"Wavelet transform of SAR images for internal wave detection and orientation","authors":"J. Ródenas, R. Garello, D. Cabarrocas","doi":"10.1109/ICIP.1997.648095","DOIUrl":null,"url":null,"abstract":"An efficient computational framework for the extraction of mesoscale features, i.e. internal waves, present in SAR images is discussed. A method for coastline detection based on a sequence of basic-processing procedures followed by a contour tracing algorithm is also introduced in order to obtain sea-land separation to enhance the internal wave detection problem. The utility of wavelet analysis as a tool for automatic oceanic internal wave detection and orientation from SAR images is examined using the 2-D wavelet transform based on the local modulus maxima. We show that the evolution of wavelet local maxima across scales characterize the local shape of these quasi-linear structures. The results from this study show that wavelet analysis is an excellent tool to detect internal waves from satellite images against internal wave lookalikes.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"C-25 1","pages":"841-844 vol.1"},"PeriodicalIF":0.0000,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.1997.648095","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
An efficient computational framework for the extraction of mesoscale features, i.e. internal waves, present in SAR images is discussed. A method for coastline detection based on a sequence of basic-processing procedures followed by a contour tracing algorithm is also introduced in order to obtain sea-land separation to enhance the internal wave detection problem. The utility of wavelet analysis as a tool for automatic oceanic internal wave detection and orientation from SAR images is examined using the 2-D wavelet transform based on the local modulus maxima. We show that the evolution of wavelet local maxima across scales characterize the local shape of these quasi-linear structures. The results from this study show that wavelet analysis is an excellent tool to detect internal waves from satellite images against internal wave lookalikes.