Image quality assessment using log-Gabor Weber feature

As human eye perception for the brightness accords with the Weber's law, this paper uses the log Gabor filter to simulate the human eye perception for an image and proposes a new log Gabor Weber characteristics to keep the structural information interested by human for different scales. To assess the image quality more effectively, a new image quality assessment method was proposed by using log-Gabor Weber feature. The log-Gabor filter and Weber's law were used to obtain a new feature named log-Gabor Weber feature (LGW). Firstly, the distorted image and reference image were transformed from the RGB color space into a YIQ color space to separate the luminance component and the chromatic component. Then, the LGW feature and gradient feature were used to calculate the distortion of luminance component. Furthermore, the distortion of chromatic component was integrated to get the local similarity map between distorted image and reference image. Finally, a modified CSF pooling strategy was applied to the overall local similarity map to obtain the final image quality index. The experimental results on three benchmark image databases, LIVE, CSIQ and IVC, indicate that the proposed method owns a good consistency with human subjective perception and it has a more stable performance as compared with other state-of-the-art methods. The weighted Spearman Rank Order Correlation Coefficient(SROCC), Kendallrank-order Correlation Coefficient (KROCC) and the Pearsonlinear Correlation Coefficient, PLCC) values on three databases by the proposed method are 0.949 8, 0.802 6 and 0.943 8, respectively, which notably outperform other methods. © 2015, SCIENCE PRESS. All right reserved.