The invention discloses an image adaptive reduction method by using minimum entropy to judge visual perception saturation. The method comprises the following steps: 1) by using different reduction multipliers Ki, down sampling is carried out on an original image, and multiple reduction images Ii are constructed; 2) as for the Ii, a salient point prediction algorithm is used to calculate a salientimage Si, wherein a pixel point with the salience value larger than an average value is used as a fixation point; 3) a fixation area is formed by the fixation points, the centroid of the area is solved, and the frequency of a fixation point with a different distance away from the centroid point is counted; 4) the entropy Ei generated by the distance between a fixation point and the centroid in each reduction image is calculated; and 5) the Ei under a different reduction multiplier Ki is compared, and the Ki corresponding to the minimum value is the best reduction multiplier. The entropy is introduced and a human visual mechanism is used to automatically select an appropriate image reduction scale, thereby reducing a data amount and improving the algorithm performance.
Image adaptive reduction method by using minimum entropy to judge visual perception saturation