Visual Saliency Using Binary Spectrum of Walsh–Hadamard Transform and Its Applications to Ship Detection in Multispectral Imagery

Abstract

Detection of visual saliency is valuable for applications like robot navigation, adaptive image compression, and object recognition. In this paper, we propose a fast frequency domain visual saliency method by use of the binary spectrum of Walsh---Hadamard transform (WHT). The method achieves saliency detection by simply exploiting the WHT components of the scene under view. Unlike space domain-based approaches, our method performs the cortical center-surround suppression in frequency domain and thus has implicit biological plausibility. By virtue of simplicity and speed of the WHT, the proposed method is very simple and fast in computation, and outperforms existing state-of-the-art saliency detection methods, when evaluated by using the capability of eye fixation prediction. In arduous tasks of ship detection in multispectral imagery, large amount of multispectral data require real-time processing and analyzing. As a very fast and effective technique for saliency detection, the proposed method is modified and applied to automatic ship detection in multispectral imagery. The robustness of the method against sea clutters is further proved.