Saliency Detection For Small Maritime Target Using Singular Value Decomposition Of Amplitude Spectrum

Spectrum analysis based saliency detection approaches have been studied and applied in computer vision. They are either generalized filtering or spectrum whitening of amplitude spectrum of image. However, as resultant salient regions may be inconsistent, a better result can be achieved by combining several scales. This paper proposes a novel saliency detection method for small maritime target using singular value decomposition (SVD) of amplitude spectrum. Color and intensity features of image are extracted and Fourier transform is employed on them. SVD is conducted on amplitude spectrums of each feature and their saliency maps are defined as the inverse Fourier transform of non-dominant components, whose amplitude spectrum is measured by difference between original amplitude spectrums and their main components. Taking into account the characteristics of maritime visual scene, the dominant parts of amplitude spectrum are selected according to threshold which is the ratio of singular values. Color saliency map and intensity saliency map are linearly combined to achieve the saliency map. The proposed method is conducted on the original image size, thus maintaining information of small maritime target. Experiments are made to show the validity and effectiveness. Comparison between proposed method and related approaches demonstrates that the new method is more suitable for saliency detection of small maritime target. Effect of threshold is also analyzed, and 50% is best for saliency detection of small maritime targets. The new saliency detection approach can be used for small maritime target detection and tracking.