Techniques for multiresolution image registration in the presence of occlusions

This paper describes and compares techniques for registering an image with respect to a template image when one or both are partially occluded. These techniques can be used to build correlation-based image registration (alignment of similar images) and image search (finding a sub-image within a larger image) algorithms. Binary masks as developed by Stone and Shamoon [18], and extended by Stone [15] to multi-resolution images, allow exact comparison of partially occluded images. Fractional masks, introduced in this paper, extend this idea for better discrimination on low-resolution images. The low and multi-resolution images result from searching the low-pass subbands of wavelet representations of images. By operating on low-resolution images and computing the correlation function in the frequency domain, the mask based algorithms can be implemented efficiently. We present experimental evidence supporting the use of occlusion masks in the registration process and find that binary masks produce higher registration peaks while fractional masks produce sharper peaks.