Mathematical elements for computer graphics (2nd ed.)
Mathematical elements for computer graphics (2nd ed.)
Improved estimation of clutter properties in speckled imagery
Computational Statistics & Data Analysis
Contrast Definition for Optical Coherent Polarimetric Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
M-estimators of roughness and scale for GA0-modelled SAR imagery
EURASIP Journal on Applied Signal Processing
Analysis of minute features in speckled imagery with maximum likelihood estimation
EURASIP Journal on Applied Signal Processing
Accuracy of edge detection methods with local information in speckled imagery
Statistics and Computing
In Situ Image Segmentation Using the Convexity of Illumination Distribution of the Light Sources
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Image Processing
Two-dimensional extension of variance-based thresholding for image segmentation
Multidimensional Systems and Signal Processing
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We present an approach for polarimetric Synthetic Aperture Radar (SAR) image region boundary detection based on the use of B-Spline active contours and a new model for polarimetric SAR data: the $${\mathcal{G}_P^H}$$ distribution. In order to detect the boundary of a region, initial B-Spline curves are specified, either automatically or manually, and the proposed algorithm uses a deformable contours technique to find the boundary. In doing this, the parameters of the polarimetric $${\mathcal{G}_P^H}$$ model for the data are estimated, in order to find the transition points between the region being segmented and the surrounding area. This is a local algorithm since it works only on the region to be segmented. Results of its performance are presented.