A psychovisually-based image quality evaluator for JPEG images

We propose an algorithm for evaluating the quality of JPEG compressed images, called the psychovisually-based image quality evaluator (PIQE), which measures the severity of artifacts produced by JPEG compression. The PIQE evaluates the image quality using two psychovisually-based fidelity criteria: blockiness and similarity. The blockiness is an index that measures the patterned square artifact created as a by-product of the lossy DCT-based compression technique used by JPEG and MPEG. The similarity measures the perceivable detail remaining after compression. The blockiness and similarity are combined into a single PIQE index used to assess quality. The PIQE model is tuned by using subjective assessment results of five subjects on six sets of images. The results show that the PIQE model is most accurate in the compression range for which JPEG is most effective