Boundary detection in speckle images
Alan Conrad Bovik, D.C. Munson · 2005
Optimal statistical procedures are formulated for detecting object boundaries in speckle noise imagery. Although speckle noise is found in many applications, our principal interest is in synthetic aperture radar (SAR). The first procedure described is parametric. The ratio of local neighborhood averages is thresholded, which is a statistically natural approach since the noise is often modeled as multiplicative. A nonparametric procedure based on a linear rank statistic is also described, which can be shown to be locally most powerful (among rank tests). Examples are given, and comparisons are offered. The parametric scheme performed slightly better than the rank-order method in the examples, but the inherent robustness of the latter may recommend it for the practical application.