PSNR(peak signal noise ratio) is the common criterion used to assess the distortion of signal.But big error maybe generated with PSNR which does not involve the content of signal when used to assess image quality.SSIM(structural similarity) is used to evaluate the similarity between the source signal and the processed signal.SSIM is simple and well correlated with subject evaluation.This paper

PSNR and SSIM are combined to set up the image quality assessing model.Cluster analysis is used to make the samples data cluster into different kinds.Support Vector Machines Classifier is used to class any image into different kinds according to PSNR and SSIM.The quality of the image with different kinds is assessed with different strategy.The results from our test show the model output can reflect the image subjective quality effectively.