**3.2 A review of the attention-based methods**

The above mentioned compression methods tend to distribute the coding resources evenly in an image. On the contrary, attention-based methods encode visually salient regions with high priority, while treating less interesting regions with low priority (Figure 11). The aim of these methods is to achieve compression without significant degradation of perceived quality.

Saliency-based methods derive from biological properties of the human eye, that enable one to focus only on a limited region of an image at a time. It is thus a subjective notion, but a lot of research has been devoted to its modeling and quantification.

In the following there is an attempt to list the methods currently available in the literature, pointing to their strengths and weaknesses when possible. Although there is currently no

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Fig. 11. Illustration of the distortions introduced by general compression methods (three first images on the left) compared to saliency-based compression (three last images on the right), at three different compression levels. Adapted from Yu & Lisin (2009))

unified taxonomy, we have divided the methods into interactive, indirect and direct, the latter being the most commonly studied.
