Bottom-Up Saliency Detection Model Based on Amplitude Spectrum

Abstract

In this paper, we propose a saliency detection model based on amplitude spectrum. The proposed model first divides the input image into small patches, and then uses the amplitude spectrum of the Quaternion Fourier Transform (QFT) to represent the color, intensity and orientation distributions for each patch. The saliency for each patch is determined by two factors: the difference between amplitude spectrums of the patch and its neighbor patches and the Euclidian distance of the associated patches. The novel saliency measure for image patches by using amplitude spectrum of QFT proves promising, as the experiment results show that this saliency detection model performs better than the relevant existing models.