Image quality assessment based on complex number representation of image structure and singular value decomposition

In order to accentuate the complicated information that human eyes are sensitive to in an image,complex matrix is used to describe image structure.Local variance and pixel value are taken as the real part and imaginary,respectively.Singular value decomposition is performed on each block of the complex matrix,but standard deviation of the singular value distribution is used as the description of the image block.The standard deviation is calculated for the reference image and distorted image,respectively.The matrix composed of standard deviations corresponding to each block is used to obtain the distortion map.Quantified results are obtained by calculating the data distribution of the map.779 distorted images in the LIVE database are used to test the performance of the proposed method.Experimental results show that the performance improvement is achieved by using complex matrix to describe image structure,which balances the distortion sensitivity.Consistency with the human visual perception of the proposed method is better than that of traditional methods.