An Opinion-unaware Blind Quality Assessment Algorithm for Multiply Distorted Images

摘要

The blind image quality assessment algorithms produced every year are mostly “opinion-aware” (OA). It means thatthey require large numbers of subjective quality scores for regression model training. Subjective quality scores are noteasily available, so people are eager to design an opinion-unaware (OU) algorithm which has free subjective qualityscores. Besides, the OU algorithm has greater generalization capability than the OA algorithm. Therefore, we propose anOU algorithm based on a visual codebook for multiply distorted image quality assessment. Extensive experimentsconducted on the three databases demonstrate that the proposed method is superior to the existing five OU methods interms of the coherence with the human subjective rating. The MATLAB code is available at https://tonglewang.github.io.