Image matching based on multiscale increment sign correlation and iterative correction

By combining wavelet transform and increment sign correlation with iterative correction, we present a robust image matching method, which effectively reduced mismatch. Firstly, by decomposing the sensed image and the reference image with wavelet, smooth images are generated in coarse scales. By the use of increment and decrement information of adjacent pixels, smooth images are encoded into binary images, and the matching position can be found by use of the cross correlation function. Wavelet decomposition can effectively remove noise and greatly improve the real-time performance of matching algorithm while increment sign correlation method is not sensitive to the gray level of images. The combination of wavelet transform and increment sign correlation can deal with noise, shadow and occlusion as well as improve the matching speed compared with traditional matching methods. Considering the condition of heavy noise and occlusion that the matching method mentioned above can not find the correct position in condition of heavy noise and occlusion, we present an iterative correction image matching method, i.e. use the above matching result as prior knowledge and achieve the correct matching position by correcting matching results iteratively. Theoretical analysis shows the feasibility of the presented method, and our experiments show its validity.