The baseline salience (BS) model (referred to as Itti's model in some literature) refers to the classical bottom-up visual attention model for still images, proposed by Itti et al. , and its variations have been explored in [3–5, 11, 12]. Their core modules are shown in Figure 3.1.
In Figure 3.1 the low-level features of an input still image for three channels (intensity, colour and orientation) are extracted and each channel is decomposed into a pyramid with nine scales. The centre–surround processing between different scales is performed to create several feature maps for each channel. Then fusing of across-scale and normalization for these channels produces three conspicuity maps. Finally, the three conspicuity maps are combined into a saliency map of the visual field. As mentioned above, the saliency map is the computational result of the attention model.
There are five characteristics of the core of this bottom-up visual attention model: