The method of spectral residual analysis is adopted to get the global features’ saliency map, and the wavelet transforms’ local feature information representation ability in the time domain and frequency domain is used to remove redundant information and get local features highlights. The two ways are combined to get the final-saliency map and block out the saliency target. Experimental results show that the detection accuracy is improved by using the proposed method.