Extraction method of visual saliency area based on monocular depth map

The invention discloses an extraction method of a visual saliency area based on a monocular depth map. The extraction method of the visual saliency area comprises the following sequential steps: dividing an original image to obtain super pixels; building a characteristic vector of each super pixel to estimate an absolute depth characteristic of absolute depth in a scene in the image; building a probability model by using a Gaussian-Markov random field model, calculating a distance relation between the super pixel characteristic vector and an adjacent super pixel characteristic vector by virtue of the probability model to obtain a relative depth characteristic on the basis of the absolute depth characteristic and obtain depth values and depth maps of the super pixels simultaneously; calculating saliency values of the super pixels; calculating a gain coefficient according to the depth values and correcting the saliency values by using the gain coefficient. The extraction method can be used for quickly and automatically identifying the saliency objects in the image without any prior knowledge, is high in universality and can also be used for accurately detecting the saliency area.