Based on the statistical properties of mean subtracted contrast normal ized (MSCN) coefficient and the correlation between MSCN neighborhood coefficients along 8directions,a general -purpose no-reference image quality assessment(NR-IQA) method is proposed.Firstly,asymmetric generalized gaussian distribution (AGGD) models are used to fit MSCN coefficient and its neighborhood coefficients along 8directions respectively,and the parameters of those AGGD models are estimated as the statistical characteristics of luminance.Secondly,the mutual information (MI) between neighborhood MSCN coefficients along 8directions are calculated as the statistical characteristics of directional correlation.Moreover,support vector regression (SVR) and support vector classifier (SVC) are used to construct the NR-IQA model and the image distortio n type recognition model,respectively.At last,in order to analyze the correlation with differential mean opinion score (DMOS),the classification accuracy and the computational complexit y,a large number of simulation experiments are carried out in the LIVE image quality evaluation database.The simulation re sults show that this method is suitable for many common distortions and consistent with subjective assessment, and the Spearman′s rank ordered correlation coefficient (SROCC) and the Pearson ′s linear correlation coefficient (PLCC) in LIVE image quality evaluation database are more than 0.945.In addition,the recognit ion accuracy of the recognition model is up to 92.95% and significantly superior to all present NR-IQA methods.