Least Squares and Robust Estimation of Local Image Structure

摘要

Linear scale space methodology uses Gaussian probes at scale s to observe the differential structure. In observing the differential image structure through the Gaussian derivative probes at scale s we implicitly construct the Taylor series expansion of the smoothed image. The Gaussian facet model, as a generalization of the classic Haralick facet model, constructs a polynomial approximation of the unsmoothed image. The measured differential structure therefore is closer to the ‘real’ structure than the differential structure measured using Gaussian derivatives.