Underwater Target Recognition via Cayley-Klein Measure and Shape Prior Information in Hyperspectral Imaging

Underwater target detection plays a vital role in various application scenarios, ranging from scientific research to military and industrial operations. In this paper, method via the Cayley–Klein measure prior information of shape is proposed for issue hyperspectral underwater identification. Firstly, by analyzing data features targets backgrounds, background suppression algorithm based on developed enhance differentiation between backgrounds. Then, local peak-based designed discriminate potential points peak targets. Finally, pseudo-target are eliminated priori Experiments show that efficient can effectively detect images.