  This paper deals with a reduced reference (RR) image quality measure based on
natural image statistics modeling. For this purpose, Tetrolet transform is used
since it provides a convenient way to capture local geometric structures. This
transform is applied to both reference and distorted images. Then, Gaussian
Scale Mixture (GSM) is proposed to model subbands in order to take account
statistical dependencies between tetrolet coefficients. In order to quantify
the visual degradation, a measure based on Kullback Leibler Divergence (KLD) is
provided. The proposed measure was tested on the Cornell VCL A-57 dataset and
compared with other measures according to FR-TV1 VQEG framework.
