A two-stage framework for blind image quality assessment
Most present day no-reference/blind image quality assessment (NR IQA) algorithms are distortion specific - i.e., they assume that the distortion affecting the image is known. Here we propose a novel two stage framework for distortion-independent blind image quality assessment based on natural scene statistics (NSS). The proposed framework is modular in that it can be extended beyond the distortion-pool considered here, and each module proposed can be replaced by better-performing ones in the future. We describe a 4-distortion demonstration of the proposed framework and show that it performs competitively with the full-reference peak-signal-to-noise-ratio on the LIVE IQA database. A software release of the proposed index has been made available online: http://live.ece.utexas.edu/research/quality/BIQI_4D_release.zip.