Aimed at some large-size aerial images, a fast and effective feature point matching method is proposed In this paper, we use the feature point extracting method with the combination of Laplacian pyramid and a specified non-uniform N-dimensional directional filter to realize image filtering and extract the local extreme points.The direction and the scale information can be kept while making quick extraction of the feature points.Then we apply a binary descriptor to depict feature points in different scales, and the distance of descriptors can be quickly computed by XOR operation.Using a specified threshold to avoid mismatching, applying RANSAC to eliminate mismatching points, the paper presents experimental results to show that the proposed method is efficient for large-size aerial image with the assurance of the matching rate and accuracy.
SHI Xiang-bin, ZHANG Jin-song, LIU Jin-li, CHEN Run-feng
. A feature point matching method for large-size aerial image[J]. Journal of Shenyang Aerospace University, 2013
, 30(4)
: 40
-46
.
DOI: 10.3969/j.issn.2095-1248.2013.04.009
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