Blind blockiness measure based on marginal distribution of wavelet coefficient and saliency

The objective measurement of blockiness plays an important role in many applications, such as the quality assessment of an image, and the design of image and video coding system. However, most of the existing no-reference blockiness metrics do not consider important influences of grid distortion of an image on the performance of the metric. In this paper, we propose a new blockiness metric, which is robust to grid distortion, based on the marginal distribution of local wavelet coefficients and saliency information. Experiments for several public image databases showed that the proposed metric provides consistent correlations with subjective blockiness scores and outperforms other existing no-reference blockiness metrics.