The work aims to solve the problem that the blurred image of digital printing multiply distorted quality assessment algorithm has low consistency with the subjective evaluation of human perception. Key characteristics including entropy, brightness variance, frequency entropy and the high frequency coefficient singular value change were extracted from distorted image in spatial and frequency domain based on the idea of SSEQ algorithm to establish the no-reference image quality assessment method with support vector machine in this paper. 25 images were verified objectively and the SROCC coefficient and PLCC coefficient of the objective calculation score and the subjective evaluation score of the algorithm were 0.94 and 0.93 respectively, with high subjective and objective consistency. The algorithm is in good subjective consistency with the ocular perception and suited for the printed image quality assessment.