No-reference image quality assessment for photographic images of consumer device
In this paper we study common, camera-specific kinds of distortions and propose a no-reference image quality assessment algorithm for photographic images produced by consumer devices. Those real consumer-type images, being different from simulated-distortion images, are with realistic artifacts and quality ranges. We find that the state-of-the-art no-reference image quality assessment approaches do not perform well on those photographic images, and propose an approach that achieves high prediction performance on a dataset of consumer-centric images. The proposed method, with no need for the original image, is able to reveal camera-specific problems and differentiate consumer cameras.