Wavelet transform of SAR images for internal wave detection and orientation

J. Ródenas, R. Garello, D. Cabarrocas
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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.
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小波变换在SAR图像内波检测与定位中的应用
讨论了一种提取SAR图像中尺度特征(即内波)的有效计算框架。本文还介绍了一种基于一系列基本处理程序和轮廓跟踪算法的海岸线检测方法,以获得海陆分离,从而增强内波检测问题。利用基于局部模极大值的二维小波变换,研究了小波分析作为SAR图像海洋内波自动探测和定位工具的实用性。我们证明了小波局部极大值在尺度上的演化表征了这些准线性结构的局部形状。本研究结果表明,小波分析是一种很好的工具,可以从卫星图像中检测出内波和内波。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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Computer Analysis of Images and Patterns: 19th International Conference, CAIP 2021, Virtual Event, September 28–30, 2021, Proceedings, Part I Computer Analysis of Images and Patterns: 19th International Conference, CAIP 2021, Virtual Event, September 28–30, 2021, Proceedings, Part II Computer Analysis of Images and Patterns: CAIP 2019 International Workshops, ViMaBi and DL-UAV, Salerno, Italy, September 6, 2019, Proceedings Computer Analysis of Images and Patterns: 18th International Conference, CAIP 2019, Salerno, Italy, September 3–5, 2019, Proceedings, Part I Computer Analysis of Images and Patterns: 18th International Conference, CAIP 2019, Salerno, Italy, September 3–5, 2019, Proceedings, Part II
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