In order to make the interest target prominent, a saliency detection method based on feature fusion is proposed. Firstly, by extracting the different characteristics of different scale space in the visible image, different concatenated characteristics among scale space were fused by using the theory of regional covariance; finally by combining the global kernel density estimation, the global saliency of the image was reflected. Thus the image target saliency detection was realized by fusing the global and local features. Experimental results show that, regardless of the subjective assessment, or the objective indicators, the proposed method is superior to usual saliency detection methods.