A Kind of No Reference Image Quality Assessment Method for Blurred Images
FU Ya · Science Technology and Engineering · 2014
Considering that many no reference image quality assessment methods cannot give better assessment results for blurred images,a no-reference image quality assessment method is proposed which has better assessment results.And at the same time the structural similarity(SSIM) index is introduced into no-reference image quality assessment for broadening the application scope of the method and solving the flaw that the SSIM cannot be reasonable evaluation the blurred image quality.This method firstly constructs a reference image by a low-pass filter and calculates the structural similarity between the blurred image and the reference image,and then extracts texture features of images to compute the texture similarity between the blurred image and the reference image.Finally,with these texture similarity and structural similarity as the input factors,the subjective assessment value DMOS provided by LIVE database as the output factor,a [2 9 1]back-propagation(BP) neural network prediction model is built.Experiments indicate that the prediction results show stability and little difference from the experimental data.Their Correlation Coefficients are all above 0.97.