Spectral matching algorithm based on nonsubsampled contourlet transform and scale-invariant feature transform

Abstract

A new spectral matching algorithm is proposed by using nonsubsampled contourlet transform and scale-invariant feature transform. The nonsubsampled contourlet transform is used to decompose an image into a low frequency image and several high frequency images, and the scale-invariant feature transform is employed to extract feature points from the low frequency image. A proximity matrix is constructed for the feature points of two related images. By singular value decomposition of the proximity matrix, a matching matrix (or matching result) reflecting the matching degree among feature points is obtained. Experimental results indicate that the proposed algorithm can reduce time complexity and possess a higher accuracy.