It is often desirable to evaluate an image based on its quality. For many computer vision applications, a perceptually meaningful measure is the most relevant for evaluation; howe...
In this paper, we present an efficient general-purpose objective no-reference (NR) image quality assessment (IQA) framework based on unsupervised feature learning. The goal is to...
We study the problem of automatic “reduced reference” image quality assessment algorithms from the point of view of image information change. Algorithms that measure differenc...
In this paper, we present a no-reference video quality metric that blindly estimates the quality of a video. The proposed approach makes use of a data hiding technique to embed a ...
Marco Carli, Mylene Christine Queiroz de Farias, E...
A number of image quality metrics are based on psychophysical models of the human visual system. We propose a new framework for image quality assessment, gathering three indexes de...
Roland Brémond, Jean-Philippe Tarel, Eric Dumont...