The invention discloses a textural feature and color feature fusion-based image saliency detection method, and mainly aims at solving the problem that the textural feature utilization is insufficient and the high-texture image saliency detection result is relatively bad in the prior art. The scheme is that the method comprises the following steps of: 1) inputting an image and removing textures of the image by utilizing a total variation model-based filtering method so as to obtain an image with color textures; 2) filtering the input image by utilizing a Garbor filter so as to obtain an image with image texture information; 3) calculating a preliminary contrast value according to the image with the color features; 4) calculating a background probability according to the image with the texture information; and 5) fusing the preliminary contrast value and the background probability to obtain a new contrast and then obtaining a saliency map on the basis of color and texture features. According to the method disclosed by the invention, the color and texture information of the image is sufficiently utilized, so that the complicated-texture image detection effect is improved; and the method can be applied to computer vision tasks.