Image quality assessment based on gradient complex matrix

An image quality assessment model based on gradient complex matrix is proposed. The vertical and horizontal gradient information of grayscale image is calculated. Complex number is used to construct the measuring matrix. Singular value decomposition is performed in order to obtain the main structure information of the image. The singular value feature vectors of the image gradient complex matrices corresponding to the reference image and the distorted image are used to measure the structural similarity of the two images. PSNR is taken as a tool to evaluate the gradient distribution similarity. Their properties are analyzed by using LIVE database and nonlinearity regression function.