There are many uses of an image quality measure. It is often used to evaluate the effectiveness of an image processing
algorithm, yet there is no one widely used objective measure. In many papers, the mean squared error (MSE) or peak
signal to noise ratio (PSNR) are used. Though these measures are well understood and easy to implement, they do not
correlate well with perceived image quality. This paper will present an image quality metric that analyzes image
structure rather than entirely on pixels. It extracts image structure with the use of quadtree decomposition. A similarity
comparison function based on contrast, luminance, and structure will be presented.
Eric P. Lam, Eric P. Lam,
"Image quality measure via a quadtree homogeneity analysis", Proc. SPIE 6575, Visual Information Processing XVI, 65750R (25 April 2007); doi: 10.1117/12.719077; https://doi.org/10.1117/12.719077