2D mel-cepstrum based saliency detection

Studies on the Human Visual System (HVS) have demonstrated that human eyes are more attentive to spatial or spectral components with irregularities on the scene. This fact was modeled differently in many computational methods such as saliency residual (SR) approach, which tries to find the irregularity of frequency components by subtracting average filtered and original amplitude spectra. However, studies showed that the high frequency components have more effect on the HVS perception. In this paper, we propose a 2D mel-cepstrum based spectral residual saliency detection model (MCSR) to provide perceptually meaningful and more informative saliency map with less redundancy and without down-sampling as in saliency residual approach. Experimental results demonstrate that proposed MCSR model can yield promising results compared to the relevant state of the art models.