Feature Detection and Description in Remote Sensing Images using a Hybrid Feature Detector

Abstract

Feature detection plays a crucial role in image registration. There exists quite a few feature detection algorithms in literature like BRISK, FAST, SURF etc [14]. Each of these algorithms has its own advantages and disadvantages. BRISK is rotation and scale invariant, but it takes more time to detect the feature points. On the other hand FAST, as the name suggests, takes less time to detect the key points, but it is not scale invariant. To overcome the demerits of BRISK and FAST feature detection algorithms, this paper proposes a hybrid feature detection algorithm, which consumes less time to detect the feature key points and it is also rotation and scale invariant. This paper also focus on a comparative analysis of BRISK, FAST and proposed algorithm in terms of time to detect feature points. This paper has taken five feature key points in every Remote-sensing images and also deals with feature detection using the above three algorithms. It can be observed from the results and tables that in case of hybrid feature detector, it takes less time to detect five feature points.