Gradient Structural Similarity Image Assessment Index Based on Dilation
Sang Qing-bin · 2014
The traditional gradient structure similarity algorithm(GSSIM)simply takes the average of each sub-block GSSIM index as quality evaluation of the whole image.The human visual sensitivity is different when observing the different areas,which is ignored by GSSIM.So an approach of weighted gradient structural similarity based on dilation and image block classification was proposed for image quality assessment.In our new method,firstly the distorted image is divided into two regions:edge dilation region and smooth region.Then the distorted image is divided into 8×8image blocks,which are classified into edge dilation blocks and smooth ones according to the distorted region.The GSSIM index is given different weight values according to different type blocks.The whole image quality is calculated by Weighted GSSIM index.Experimental results on three simulated databases show that the proposed metric is more reasonable and stable than other methods.It obtains high correlations with subjective quality evaluations and low calculation,and is more consistent with human visual system.