Quality assessment for out-of-focus blurred images

During the process of image acquisition, images are often subject to out-of-focus or defocus blur because of the improper adjustment of the camera´s focal length, this image blur will degrade the image quality. However, in the literature, image quality assessment (IQA) methods dedicated to evaluating the quality of images with out-of-focus blur remain few. Therefore, in this paper, we focus our attention on the quality assessment of images that suffer from out-of-focus blur and propose an objective quality assessment method accordingly. Concretely, we construct a dedicated out-of-focus blurred image dataset, which is composed of 150 images subjected to different degrees of out-of-focus blur and the mean opinion scores (MOSs). Then, we propose a specific objective quality metric for the blurred images, which combines image sharpness assessment and saliency-guided pooling strategy. Experimental results demonstrate the proposed metric highly correlates with human judgements of image quality.