A panoramic image saliency detection method based on regional growth and an eye movement model. The regional growth and a fixed prediction model are used to realize detection of an automatic salient object of a panoramic image. The method comprises: detecting an original image based on regional growth, and roughly extracting an area with a significant density difference compared with a neighbor area by means of a regional growth algorithm to obtain an area with a large density difference; obtaining a saliency value of a salient region by means of eye movement fixed point prediction; carrying out maximum value normalization and then carrying out summing; and enhancing the salient region more uniformly by using a method for optimizing a geodesic line. According to the method, the problems that an existing method has insufficient saliency detection precision and robustness and is not suitable for the panoramic image can be solved, thus the salient region in the panoramic image is more accurately displayed, and accurate and useful information is provided for the later application of target recognition, classification and the like.
PANORAMIC IMAGE SALIENCY DETECTION METHOD BASED ON REGIONAL GROWTH AND EYE MOVEMENT MODEL