Visible and infrared image registration algorithm based on NSCT and gradient mirroring

Abstract

Multi-sensor image registration is an important part of the remote sensing image processing. The gray property of the same object would have large differences in infrared and visible imaging mode, so it could get less matching points by using traditional SIFT algorithm directly in registration. However, NSCT decomposition can represent the structural information of the image very well and extract more SIFT feature points in its high frequency decomposed image. In addition, traditional SIFT descriptors' gradient is affected by gray contrast, which could get less feature matching points during the similarity search in the matching procedure. Gradient mirroring (GM) is a method that can modify the direction of the feature points, which can reduce the contrast impact on the similarity matching. Therefore, a novel method combining NSCT and GM is proposed in this article. The experiments prove that, comparing with the traditional SIFT algorithm, the new method can get more matching points, better distributing and higher matching rate in infrared and visible image registration.