Fig. 2

The framework of the proposed approach. First, the RGB color reference and distorted images are converted into YIQ color space. The luminance channel of reference and distorted images are divided into edge and texture components. Then, the mean and standard deviation of texture component are used to evaluate the local luminance and contrast similarity; the gradient magnitude of edge component is used to evaluate the local structural similarity. The effects of the changes in edge and texture are integrated using different weight methods to obtain the local image quality score. Moreover, I and Q, two chrominance channels, are used as features to characterize the quality degradation caused by color distortions. Finally, the texture component is employed as a weighting function to derive a single similarity score