Blind quality assessment of JPEG2000 compressed images using natural scene statistics

摘要: Measurement of image quality is crucial for many image-processing algorithms, such as acquisition, compression, restoration, enhancement and reproduction. Traditionally, researchers in assessment have focused on equating with similarity to a 'reference' or 'perfect' image. The field blind, no-reference, assessment, which predicted without the reference image, has been largely unexplored. In this paper, we present blind algorithm images compressed by JPEG2000 using natural scene statistics (NSS) modelling. We show how reasonably comprehensive NSS models can help us making but accurate, predictions quality. Our performs close limit imposed useful prediction variability between human subjects.