Precise image matching via multi-resolution analysis and least square optimization
LI Jie
LIU Yi-guang
DU Shuang-li
XU Zhen-yu
Abstract：When subjected to the large scale, large rotation and large translation, the classic log polar mapping based Fourier transform (LPMFT) suffers from misregistration. Motivated by this problem, a novel approach named multi-resolution analysis and least square optimization (MALSO) is proposed: firstly, original images are decomposed into multi-resolution levels by wavelet transform, and only the low frequency part of each level is chosen as the matching candidate; secondly, to alleviate the influence caused by leakage, aliasing and interpolation error, in each level, window function and adaptive filtering technique are introduced into LPMFT;finally, for obtaining a set of optimal parameters, a cost function is carefully established which is approximated by least square optimization method. Experimental results show that the proposed approach not only minimizes the influence of the large scale, large rotation and large translation, but also achieves a better registration performance than the classic LPMFT method for occlusion image pairs.
Keywords：image matchinglarge similarity transformationmulti-resolutionlog-polar mapping based Fourier trans-formleast square
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：9( 811-819 )