Improved algorithm for no-reference quality assessment of blurred image
LI Hong-li · Journal of Computer Applications · 2014
A fast and effective quality assessment algorithm of no-reference blurred image based on improving the classic Repeat blur( Reblur) processing algorithm was proposed for the high computational cost in traditional methods. The proposed algorithm took into account the human visual system, selected the image blocks that human was interested in instead of the entire image using the local variance, constructed blurred image blocks through low-pass filter, calculated the difference of the adjacent pixels between the original and the blurred image blocks to obtain the original image objective quality evaluation parameters. The simulation results show that compared to the traditional method, the proposed algorithm is more consistent with the subjective evaluation results with the Pearson correlation coefficient increasing 0. 01 and less complex with half running time.