Saliency algorithm has received great attention and has been widely used in image segmentation, object recognition, etc. since Itti [33] proposed a saliency algorithm for simulating the attention mechanism of the human visual system in 1998.
The spatial attention model can simulate the visual attention mechanisms well for some sequences with simple background, such as Champagne tower and Pantomime.
Accordingly, many efforts have been devoted to researches on visual attention model [11 16] so as to simulate the visual attention mechanism of HVS accurately.
We proposed a bottom-up SVA model to simulate the visual attention mechanisms of the human visual system with stereoscopic perception.
We propose a novel SVA model, where multiple perceptual stimuli including depth, motion, intensity, color, and orientation contrast are utilized, to simulate the visual attention mechanisms of human visual system with stereoscopic perception.
IT is the earliest to use computer to simulate the biological visual attention mechanism, which mainly contrasts the color, brightness and direction of the image with the background to get a saliency image.
The visual attention model adopts the multi-scale spatial attention to simulate the nonuniform sampling mechanism of the human retina [15].
Actually, in order to accurately simulate the mechanism of human visual attention, values of parameters,, and, and,, and, should be adjusted according to motion, textual, and depth characteristics of the multiview video sequences.
After analysing the existing visual attention models, we combine the pyramid model of visual attention with singular value decomposition to simulate the human retina, which can make the visual attention model more suitable to the characteristics of SAR images.
A parameter z was included to increase the value of NP at arbitrary points to simulate the effect of media or outreach attention.
