Wavelet-based registration and compression of sets of images

Registration of images is of great importance in the fields of aerial surveillance, automatic target recognition, machine vision and medical imaging. Wavelets are tools that are being used to analyze signals and images. Wavelets in some sense are alternatives to Fourier transforms. Wavelets provide excellent time and frequency localization properties when compared to Fourier transforms. Singularities and irregular structures carry very important information about edges. Wavelets are excellent tools for detecting these singularities and characterizing the regularity of the function using Lipschitz exponents as shown by mallat et. al. In this paper we use the wavelet modulus maxima which is the strict local maxima of the modulus of the wavelet of the modulus of the wavelet transform to locate the singularities at each scale. homologous points from two similar images are then used to register the images using a best fit criteria. The objective function being that the difference image is a minimum image. The technique exploits inter image redundancy in addition to the intra image redundancy in sets of similar images after they have been registered. This lead to higher compression ratios. It also permits the use of any existing compression technique to exploit intra image redundancy.