Feature-based image fusion scheme for satellite recognition
Han Chang Pan, Gang Xiao, Zhongliang Jing · 2010
Despite the variety of technologies and algorithms studied, satellite recognition is not fully researched in the uncontrolled space environments. In this paper, a low complexity and efficient satellite recognition scheme by fusing infrared and visible image features for recognition was brought forward. Invariant moments are taken to represent the characteristics of satellites' pictures. Unlike optimal image feature fusion by classic intelligent computing algorithms, a low computation and efficient fusion rules are developed to improve the performance of recognition. Due to the compute power of space-based computer, a new fusion method by associating combined blur and affine moments invariant (CBAI) with Zernike moments is introduced. The experiments results with Semi-physical simulation images indicate that the recognition consistently demonstrated better performance than others solely based on either infrared or visible image.