  Saliency detection is one of the most challenging problems in image analysis
and computer vision. Many approaches propose different architectures based on
the psychological and biological properties of the human visual attention
system. However, there is still no abstract framework that summarizes the
existing methods. In this paper, we offered a general framework for saliency
models, which consists of five main steps: pre-processing, feature extraction,
saliency map generation, saliency map combination, and post-processing. Also,
we study different saliency models containing each level and compare their
performance. This framework helps researchers to have a comprehensive view of
studying new methods.
