Using An Image Preliminary Segmentation For Adaptive Subpixel Correlation
Sergey Yu. Zheltov, Alexander Sibiryakov · 1998
This work deals with the subpixel point correspondence problem. Subpixel matching methods such as Least-Squares Correlation [2] or Adaptive Subpixel Cross-Correlation [1] use six-parameter geometric transformation and two-parameter radiometric transformation of the whole image patches to achieve subpixel matching accuracy. However different regions inside image patch may have different distortion parameters. The method developed in this paper uses the images preliminary segmented into regions. Each region possesses its own unknown distortion parameter set that can be found by solving the correlation coefficient maximization problem. Two different kinds of correlation: widely used normalized cross-correlation and morphological correlation are to be considered. In both cases the consecutive correlation application results in problem of a finding a vector of the amendments of the parameters as a generalized eigenvector problem. The theoretical decision of this problem in view of specific structure of matrices obtained by linearization is offered.