Building Image Stereo Matching Based on Improved SIFT Algorithm
Haitao Niu, Zhao Xun-jie, Chengjin Li, Xiang Peng · Jisuanji gongcheng · 2011
On the building image processing with Scale Invarint Feature Transform(SIFT) descriptor,there will be a large number of falsely matching points.Aiming at this problem,the color and global information is introduced to improve the performance of SIFT descriptor.It introduces l1l2l3 model which is robust against light change and build log-polar coordinates.For each key point,it builds circular neighborhood to cumulate the value of l1,l2,l3.Color invariant descriptor can be constructed.Global descriptor can be constructed with the same method.The Euclidian Distances of SIFT color invariant descriptor and global descriptor will be as similarity measurement.Experimental results indicate that the improved SIFT algorithm can reduce mismatch probability of building images and improve matching results greatly.