Hierarchically adaptive image block matching under complicated illumination conditions

Abstract

Image block matching is one of active research fields in image processing, which has been widely used in security monitoring and motion estimation. Due to great disparities in images of the same scene under various illumination, block matching has been a challenging task. To this end, we propose a hierarchical block matching method which is adaptive to the computational complexity and suited to complicated illumination environments. The approach is divided into two parts. First, in order to reduce searching time, the whole algorithm is established in the framework of pyramid structures. Second, the correlation coefficient and structural functions are adopted to evaluate the similarity between two images so as to get better matching results. Simulation results show that, compared with the classical three-step, four-step searching algorithms and OHBM algorithm, this algorithm can reduce the time complexity efficiently. Moreover, since the algorithm makes use of the structure details of images, it is robust to complicated scenes.