A structured-based image similarity measure using homogeneity regions

Abstract

Comparing two similar images is often needed to evaluate the effectiveness of an image processing algorithm. But, 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. These measures rely entirely on pixel intensities. Though these measures are well understood and easy to implement, they do not correlated 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 a recursive quadtree decomposition. A similarity comparison function based on contrast, luminance, and structure will be presented.