Image quality assessment (IQA) is one of the most important issues in the field of image processing. Traditional IQA methods usually assume that the “reference” or “perfect” image is given. Obviously, this assumption is limited because the reference image may not be available in most practical applications. In addition, the mechanisms of human visual system (HVS) have not been explicitly exploited in the majority of existing IQA methods. In this article, to reduce dependence on reference image while introducing one mechanism of HVS, we propose a new method, referred to as Image-Saliency-based No-reference Image Quality Index (ISNIQI), by incorporating image saliency derived from visual attention models into the quality assessment of JPEG compressed images. Since the high saliency image region attracts more visual attention, ISNIQI assigns larger weight to the quality of image region with higher saliency. Experimental results on JPEG compressed images demonstrate the effectiveness of the proposed method in terms of the correlation with subjective perception.