J. REDI

Objective metrics for visual quality assessment usually improve their reliability by explicitly modeling the highly non-linear behavior of human perception; as a result, they often are complex, and computationally expensive. Conversely, Machine Learning (ML) paradigms allow to tackle the quality assessment task from a different perspective, as...

Imaging algorithms often require reliable methods to evaluate the quality effects of the visual artifacts that digital processing brings about. This paper adopts a no-reference objective method for predicting the perceived quality of images in a deterministic fashion. Principal Component Analysis is first used to assemble a set of objective...