SAR image segmentation based on level set approach and G⁰A model.

This paper proposes an image segmentation method for synthetic aperture radar (SAR), exploring statistical properties of SAR data to characterize image regions. We consider G⁰A distribution parameters for SAR image segmentation, combined to the level set framework. The G⁰A distribution belongs to a class of G distributions that have been successfully used to model different regions in amplitude SAR images for data modeling purpose.

Vessel network detection using contour evolution and color components.

Automated retinal screening relies on vasculature segmentation before the identification of other anatomical structures of the retina. Vasculature extraction can also be input to image quality ranking, neovascularization detection and image registration. An extensive related literature often excludes the inherent heterogeneity of ophthalmic clinical images.

Wavelet analysis for wind fields estimation.

Wind field analysis from synthetic aperture radar images allows the estimation of wind direction and speed based on image descriptors. In this paper, we propose a framework to automate wind direction retrieval based on wavelet decomposition associated with spectral processing. We extend existing undecimated wavelet transform approaches, by including à trous with B(3) spline scaling function, in addition to other wavelet bases as Gabor and Mexican-hat.