Comprehensive image quality assessment via predicting the distribution of opinion score

Image quality assessment is a challenge problem in image processing area. Previous works usually predict the mean opinion score (MOS) to evaluate image quality. However, it is found that the distribution of opinion scores provides richer and more precise semantics information. Therefore, in this work, we focus on the distribution of opinion scores (DOS) and aims to comprehensively evaluate image quality via automatically predicting DOS. Specifically, we first extract image features via convolutional neural network and then adopt the label distribution support vector regressor (LDSVR) algorithm to predict score distribution. To the best of our knowledge, we are the first to introduce label distribution learning approach for image quality assessment. Extensive experiments have been carried out and validate that the proposed algorithm can well predict the DOS and provide a comprehensive assessment to image quality.