In the practical application

image may need to be resized when to be observed

especially

in the circumstance of enlarging image resolution

the image quality would be degraded inevitably.In order to make image quality evaluation in this case

an image quality assessment algorithm based on prediction is proposed.The proposed algorithm use the cross-correlation coefficient between neighboring pixels as index.At the same time

considering the facts that a strong correlation between one pixel and its neighboring pixels would bring the fuzzy in the image edge area

so image is separated into different classification

different approach is adopted according to the different area.Meanwhile

in order to give attention of human visual system characteristics

the image multi-scale analysis is also to be embedded in the prediction algorithm.In the end

we get a more exact result score

and this score would be an index of distorted image quality score.The experiment results demonstrate that the proposed CCS algorithm can be used as a method to assess the image distorted quality

and increase the accuracy of image quality assessment comparing with conventional algorithms DIIVINE.