中文摘要：

为了有效地度量不同失真类型的图像质量，提出一种基于自然场景统计（ NSS）模型的空域无参考图像质量评价算法。该算法利用自然图像归一化亮度系数的统计特征趋向于服从广义高斯概率分布的特性，首先在空域计算自然图像的梯度，通过梯度密度选取自然图像的兴趣区域，提取兴趣区域图像统计特征，建立多元高斯分布（ MVG）模型；然后对测试图像建立同样的MVG模型；最终通过计算测试图像和自然图像在统计规律上的偏差来对测试图像的质量做出评价。实验证明该算法与主观评价具有较好的一致性。

英文摘要：

In order to measure the image quality of different distortion types, a spatial natural scene statistics （ NSS） based model of no reference image quality assessment method is proposed.The normalized brightness coefficients of natural images obey the generalized Gauss distribution and the proposed method uses these features.The proposed method can be described as follows. Firstly, the gradient values of natural images are computed in the spatial domain, the ROI （ regions of interest） of natural images are selected by gradient density, the statistical characteristics of natural images are extracted and the multivariate Gauss distribu-tion （ MVG） model is established.Secondly, the same MVG model of test images is established.At last, the quality of test ima-ges is evaluated by calculating the distance of the MVG model between test images and natural images.Experimental results show that the proposed method is more consistent with human subjective perception.