AUTOMATIC REGION SELECTION FOR OBJECTIVE SHARPNESS ASSESSMENT OF MOBILE DEVICE PHOTOS

Mobile devices are the source of a vast majority of digital photos today. Photos taken by mobile devices generally have fairly good visual quality. When evaluating high-quality mobile device photos, people have to manually zoom in to local regions to discern the subtle difference. Understandably, a global objective quality assessment method cannot perform well on such task. Therefore, local region selection is widely recognized as a prerequisite for the following quality evaluation. Clearly, subjective regions selection suffers from the drawbacks in terms of productivity, reproducibility and optimality. In this paper, we propose an automatic local region selection algorithm for sharpness measurement of mobile device photos. Specifically, local texture statistics, depth, saliency, as well as inter-pictures difference, are used as main features to select an optimal local region, in which the sharpness is then measured. For validation, we have built a largescale database for sharpness evaluation of mobile device photos, with 100 different scenes shot by several flagship mobile phones. The experimental results show that the performance of classic sharpness evaluation algorithms can be substantially improved with the region selected by the proposed algorithm.