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Multi-resolution eddy detection from ocean color and Sea Surface Temperature images ArchiMer
Karoui, Imen; Chauris, Hervé; Garreau, Pierre; Craneguy, Philippe.
We propose a multi resolution method for automatic detection of eddies on both simulated and satellite Sea Surface Temperature (SST) or ocean color images. Our approach consists in a curvelet based analysis of image fronts along circles with specified radius values. The main interests of the proposed method are: It is carried out on image gradient, and is thus not sensitive to the choice of binarization threshold; With the multi-resolution aspect and the anisotropic spatial support shape of curvelet elements, we can deal with no perfectly circular eddies (curvelet width) and we also take into account the image regularity to distinguish between real eddies and noise (curvelet length). We have tested the method on several modeled and satellite images in the...
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Ano: 2010 URL: http://archimer.ifremer.fr/doc/00068/17888/15422.pdf
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The circlet transform: A robust tool for detecting features with circular shapes ArchiMer
Chauris, H.; Karoui, Imen; Garreau, Pierre; Wackernagel, H.; Craneguy, Philippe; Bertino, L..
We present a novel method for detecting circles on digital images. This transform is called the circlet transform and can be seen as an extension of classical 1D wavelets to 2D; each basic element is a circle convolved by a 1D oscillating function. In comparison with other circle-detector methods, mainly the Hough transform, the circlet transform takes into account the finite frequency aspect of the data; a circular shape is not restricted to a circle but has a certain width. The transform operates directly on image gradient and does not need further binary segmentation. The implementation is efficient as it consists of a few fast Fourier transforms. The circlet transform is coupled with a soft-thresholding process and applied to a series of real images...
Tipo: Text Palavras-chave: Circlet transform; Circle detection; Image processing; Multi-scale representation; Computer vision.
Ano: 2011 URL: http://archimer.ifremer.fr/doc/00033/14451/11752.pdf
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