Sequential Band Fusion for Hyperspectral Target Detection

Due to the enormous data and redundant information, how to process hyperspectral images reasonably and efficiently has become a research focus. This article proposes a sequential band fusion (SBF) approach for hyperspectral target detection and gives a detailed derivation of the fusion theory. Then four fusion algorithms—SBF based on band sequence (SBF-BSQ), SBF driven by an initial band (SBF-IBD), SBF based on band priority (SBF-BP), and SBF based on band selection (SBF-BS)—are introduced for application. Experimental results prove that the method proposed in this article can not only effectively improve the efficiency of target detection but also provide the trend of the detection value during the fusion process. Band fusion breaks through the limitation of band selection in the application and provides a new processing method for hyperspectral data.