Multiresolution Matching Algorithm Based on Wavelet Transform
Wavelet Transform-based Multiresolution Matching Algorithm: This algorithm leverages wavelet multiresolution properties to decompose both the target image and template image into Z layers while preserving only the LL low-frequency components. It employs normalized correlation as a similarity metric to perform coarse-to-fine correlation matching, where each subsequent layer uses matching results from the previous layer to conduct localized searches in higher-resolution spaces. This approach significantly reduces search space and decreases computational load for similarity calculations in each matching iteration. Implementation typically involves wavelet decomposition using functions like wavedec2() in MATLAB, with correlation computed through optimized matrix operations.