Extraction of ocean eddies based on contourlet analysis and morphology

Biao Chen; Jie Chen

doi:10.1117/12.833180

30 October 2009 Extraction of ocean eddies based on contourlet analysis and morphology

Biao Chen, Jie Chen

Proceedings Volume 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications; 749821 (2009) https://doi.org/10.1117/12.833180
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

In this study, a combined algorithm using the Contourlet transform and morphology is proposed to detect the significant spatial patterns of ocean eddies. Contourlet transform, which is introduced recent years, has better performs in representation of geometry lines or curves than the wavelet transform. The source image was decomposed by Contourlet with several levles, the high-frequency images is divide into eight directions by the directional filter in each level. Then deal with the high-frequency and low-frequency coefficients separatically, use mathematical morphological method extracts edges in low-frequency approximate. At last, the two edge images were rebuilt to obtain an integrated and clear edge image. The Hough transform is than used to extract the characteristic of the eddies. The experimental results show that this algorithm cabin the priority of the Contourlet and morphological method and is superior to other traditional edge detection method such as the grads method, the Sobel method, or morphological method alone. The study verified that the algorithm proposed is an effective way to identify and detect ocean eddies with complex form.

Citation Download Citation

Biao Chen and Jie Chen "Extraction of ocean eddies based on contourlet analysis and morphology", Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 749821 (30 October 2009); https://doi.org/10.1117/12.833180

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KEYWORDS

Synthetic aperture radar

Hough transforms

Image filtering

Edge detection

Image segmentation

Linear filtering

Detection and tracking algorithms

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