Enhancement Matching Algorithms Using Fusion of Multiple Similarity Metrics for Sonar Images
Hatem Awad A. Khater, Ahmed Shehata Gad, Ehab A. Omran, Ayman A. Abdel-Fattah, Egyptian Navy · 2009
Abstract: The goal of this paper is to develop a matching technique for sonar and underwater images where it is used for a range of applications including stereo vision, classification of sonar images, underwater image registration and mosaicing,..., etc. The paper presents a novel scheme to improve the performance of image matching algorithms using a combination of independent matching similarity metrics. A number of corner similarity metrics have been developed to facilitate matching, however, any individual metric has a limited effectiveness depending on the content of images to be registered and the different types of distortions that may be present. This paper explores combining corner similarity metrics to produce more effective measures for corner matching. In particular the combination of two similarity metrics is investigated using experiments on a number of images exhibiting different types of transformations and distortions. The results suggest that a linear combination of different similarity metrics may produce more accurate and robust assessments of corner similarity. Key words: Sonar image matching Score fusion Underwater image registration