Image Mosaic Approach using Local Feature Points Registration
Guo Xiao-ra · Bandaoti guangdian · 2014
In order to solve the problems of scale,viewpoint and brightness changes,also with the noise and blurring changes in image mosaic,a novel image mosaic approach with stronger robustness was proposed.Firstly,according to the distinguishing feature of Harris algorithm and SIFT algorithm,an adaptive Harris-SIFT feature point extraction method was proposed,and most-adjacent method was used to realize coarse matching of points between images.Secondly,random sample consensus(RANSAC)algorithm was adopted to filter the coarse matching key-points,and transformation matrix under perspective collineation was estimated,at the same time image registration was executed between two adjacent images. Finally,weighted fusion algorithm was utilized to remove stitch line in the area of image mosaic, and high quality image mosaic was achieved.Experimental results demonstrate that the proposed approach can not only promote the robustness of SIFT algorithm,but also reinforce the effect of image mosaic and eliminate the impact of image brightness diversity and chrominance difference.