Our approach to blind image quality assessment (IQA) is based on the hypothesis that
natural scenes possess certain statistical properties which are altered in the presence of …

Present day no-reference/no-reference image quality assessment (NR IQA) algorithms
usually assume that the distortion affecting the image is known. This is a limiting assumption …

Sharpness metrics that use the frequency spectrum of the image cannot separate the
sharpness information from scene content. Sharpness metrics that use spatial gradients of …

Sharpness metrics that use the whole frequency spectrum of the image cannot separate the
sharpness information from the scene content. The sharpness metrics that use spatial …

Many user-end applications require an estimate of the quality of coded video or images
without having access to the original, ie a no-reference quality metric. Furthermore, in many …

In this paper we present a no-reference video quality metric based on individual
measurements of three artifacts: blockiness, blurriness, and noisiness. The set of artifact …

This chapter presents work on a no-reference objective quality metric (NROQM) that has
resulted from extensive research on impairment metrics, image feature metrics, and …

In this paper, a new no-reference (NR) objective metric based on data hiding is proposed.
The metric has the advantage of being fast and not requiring knowledge of the original video …

Most present day no-reference/blind image quality assessment (NR IQA) algorithms are
distortion specific-ie, they assume that the distortion affecting the image is known. Here we …

In the past few years, a big effort in the scientific community has been devoted to the
development of better digital video quality metrics that correlate well with the human …