Abstract
Scene matching which plays an important role in machine vision and remote sensing can be obtained from very high resolution satellite images. Although scale invariant feature transform (SIFT) is a powerful tool in scene conformation under different image status, but it is not adequate to give away a robust matching, due to the pettiness nature of objects in satellite images. In this paper, the scene matching algorithm has been modified using a combination of SIFT and bilateral filter along with a novel matching method. In this method, a bilateral filter is initially imposed on image and then the SIFT key points are extracted from the main and query image and finally imposing the proposed novel match method on the image resulted in acquiring a robust matching. Testing the method on a set of satellite images showed a vast decrease in false matching points and an enormous increase in processing speed which best satisfied the real-time requirements in comparison with results, using SIFT alone.
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