Blind DIBR-synthesized Image Quality Assessment using multi-scale DoG and GRNN

Abstract

In this paper, we explore the suitability of multi-resolution and multi-scale band-pass image representation generated by difference of Gaussian (DoG) operator for blind image quality assessment model. The developed model is based on general regression neural network (GRNN). The proposed model is consistent with human perception when evaluated on DIBR-synthesized image dataset.