关键词: 图像质量评价, 无参考, 通用型, 特征提取

Abstract: Image quality assessment can effectively evaluate distortion or degradation caused by image acquisition and transmission process, which has a broad application prospect in the field of digital multimedia. And because of no need any pristine knowledge of reference images, no-reference image quality assessment has become an advanced research hotspot in the field of image quality assessment. On the basis of extensive research of literatures at home and abroad, in both of algorithm principle and performance comparison, this paper systematically introduces several state-of-the-art no-reference IQA algorithms, such as BIQI, DIIVINE, BLIINDS, BLIINDS-II, BRISQUE, NIQE and GRNN. Firstly, the methods of feature extraction and the principle of quality assessment of each algorithm are introduced. Secondly, the algorithms above are simulated and evaluated on the LIVE image database, and the performance and execution speed of the algorithms are analyzed and compared. At last, the further research trends of no-reference image quality assessment are proposed. Although these no-reference image quality assessments reviewed in this paper have satisfactory performance, their processes of evaluating image quality heavily depend on opinion data of image quality in the image database, and there still exist some deficiencies in evaluation?performance and algorithm complexity. Therefore, it is necessary to make further study in this field.

Key words: image quality assessment, no reference, universal, feature extraction