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

摘要： 图像质量评价可有效评估图像采集和传输过程引起的失真或退化，在数字多媒体领域具有广阔的应用前景，无参考图像质量评价算法由于不需要参考图像先验知识，近年来成为图像质量评价领域研究的热点。在对国内外文献进行广泛调研的基础上，从评价算法原理和性能比较两个方面，系统综述了BIQI、DIIVINE、BLIINDS、BLIINDS-II、BRISQUE、NIQE和GRNN等当前性能较优的几种无参考图像质量评价算法。介绍了各种算法的特征提取和质量评价原理，在LIVE数据库上对上述评价方法进行仿真评估，并分析和比较了各种算法的评价性能和执行速度，提出了无参考评价方法的进一步研究方向。综述的几种无参考图像质量评价算法虽然已具有很好的效果，但在评价时严重依赖数据库中的主观评价数据，并且在评价精度和算法复杂度方面还存在一些不足，需要进行深入研究。

关键词: 图像质量评价, 无参考, 通用型, 特征提取