GPU Based Robust Image Registration for Composite Translational, Rotational and Scale Transformations

摘要

This paper presents a GPU based image registration algorithm that utilizes Hough Transform and Least Square Optimization to calculate the transformation between two images. In our approach, we calculate the transformation parameters of all possible combination solutions of matched feature points by exploiting parallel processing power of the GPU. We applied our algorithm on a variety of images including the problem of mosaic image generation. Experimental results show that our method is robust to the outliers (incorrect matches) and it can achieve very accurate registration (numeric and visual) results with much faster (up to 20 times) than CPU implementation.