A bio-inspired center-surround model for salience computation in images

作者：Sen Debashis^*; Kankanhalli Mohan

来源：Journal of Visual Communication and Image Representation, 2015, 30: 277-288.

DOI：10.1016/j.jvcir.2015.04.010

• Visual salience
• Human eye fixation
• Center-surround model
• Photoreceptor interaction
• Nonlinear combination
• Visual attention
• Bio-inspired approach
• Multi-scale filtering

A center-surround model inspired by photoreceptor interactions and visual receptive field organization is presented in this paper for salience computation that predicts human eye fixation locations in images. The essence of photoreceptor interactions is implemented considering different nonlinear combinations of responses to stimuli given by values at nearby image pixels. These combinations are then fed to difference of Gaussian filtered outputs operation and Gabor filter based processes simulating visual receptive field organization. The proposed center-surround model is used in Itti et al.'s bio-inspired framework to perform salience computation. Analysis is carried out to present the information-theoretic aspect of the nonlinear combinations. Significance of the proposed center-surround model is shown both qualitatively and quantitatively by comparing its use in salience computation with the use of existing models considering different psychological patterns, and synthetic and real-life images. Quantitative and qualitative performance of salience computation using the novel center-surround model for three well-known datasets of images are also compared to that of relevant existing salience computation approaches to demonstrate the effectiveness of the proposed approach in generating salience maps closer to human eye fixation density maps.

• 出版日期2015-7