Accurate objective quality metric is crucial for various video processing applications.Although the area of image quality assessment has attained maturity in recent years

video quality assessment still has a long way to go before it reaches the levels of success achieved by still image quality metrics.In the paper

we present a new approach to video quality assessment based quaternion singular value decomposition(QSVD)

which take the luminance

chrominance

edge energy and motion energy of each pixel as the four parts of a quaternion

and the entropy as the degree of visual interest of regions to weight each block.We demonstrate the performance of our algorithm by testing it on the Video Quality Expert Group(VQEG)Phase I FR-TV dataset

the results show that our method is competitive with state of the art quality assessment methods and has good correlation with perceived video quality.