In this paper a framework for Image Quality Assessment (IQA) is introduced based on the properties of Receptive Fields (RFs) which are the primary mechanism for detection of visua...
—We present a no-reference image quality metric for image interpolation. The approach is capable of detecting blurry regions as well as ghosting artifacts, e.g., in image based r...
Kai Berger, Christian Lipski, Christian Linz, Anit...
We present a new approach for the discriminative training
of continuous-valued Markov Random Field (MRF)
model parameters. In our approach we train the MRF
model by optimizing t...
Image quality assessment (IQA) aims to provide computational models to measure the image quality in a perceptually consistent manner. In this paper, a novel feature based IQA mode...
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...