Image enhancement quality metrics
Andrey V. Nasonov, Andrey Serdjevich Krylov · 2013
The paper presents a new adaptive full reference metrics for the quality measurement of image enhancement algorithms. The idea of the proposed metrics is to find areas related to typical artifacts of image enhancement algorithms. Two types of artifacts are considered: blur and ringing effect. The concept of basic edges is used to find areas of these artifacts which are invariant to image corruption and image enhancement methods. The metrics are illustrated with an application to image resampling and image deblurring.