No-reference quality index of tone-mapped images based on authenticity, preservation, and scene expressiveness

Abstract

As a future-proof technology, high dynamic range (HDR) has the superiority in scene reappearance. Tone mapping operator (TMO) renders the dynamic effect of HDR images in a standard dynamic range (SDR) display at the expense of some insignificant information. However, it is difficult for existing TMOs to consistently achieve high-quality conversion of all HDR images, and the loss of converted images is inevitable. Therefore, accurate prediction of tone-mapped image (TMI) quality is of considerable significance. In this paper, we propose the reappearance effect of the TMIs index (RETI). According to the characteristics of primeval HDR images, the quality of TMIs is considered from three important elements: authenticity, the preservation of energy and information, and scene expressiveness. The feature vectors originated from three elements are combined with subjective quality to train prediction model. Experiments are executed on tow mainstream TMI quality assessment databases and the results show that the proposed method has a good prediction ability and generalization ability in comparison to some state-of-the-art methods. Our MATLAB source code will be released at https://github.com/niannianyouyu/RETI.