P. Refregier et al., OPTIMAL SNAKE SEGMENTATION OF TARGET AND BACKGROUND WITH INDEPENDENT GAMMA-DENSITY PROBABILITIES, APPLICATION TO SPECKLED AND PREPROCESSED IMAGES, Optics communications, 137(4-6), 1997, pp. 382-388
We propose in this paper a snake-based segmentation processor to track
the shape of a target with random white intensity appearing on a rand
om white spatially disjoint background. We study the optimal solution
for Gamma laws and we discuss the relevance of such statistics for rea
listic situations. This algorithm, based on an active contour model (s
nakes), consists in correlations of a binary reference with the scene
image or with pre-processed version of the scene image. This method is
a generalization of correlation techniques and thus opens new applica
tions for digital and optical correlators.