Edge quality metrics for image enhancement

Authors:
A. V. Nasonov;A. S. Krylov
Affiliations:
Laboratory of Mathematical Methods of Image Processing, Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Leninskie Gory, Moscow, Russia 119991;Laboratory of Mathematical Methods of Image Processing, Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Leninskie Gory, Moscow, Russia 119991
Venue:
Pattern Recognition and Image Analysis
Year:
2012

Citing 3
Cited 0

A Ringing Metric to Evaluate the Quality of Images Restored Using Iterative Deconvolution Algorithms

ICSENG '05 Proceedings of the 18th International Conference on Systems Engineering
Adaptive Image Deblurring with Ringing Control

ICIG '09 Proceedings of the 2009 Fifth International Conference on Image and Graphics
Image quality assessment: from error visibility to structural similarity

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

The paper presents a new adaptive full reference method for quality measurement of image enhancement algorithms. The method is based on the analysis of basic edges--sharp edges which are distant from another edges. The proposed basic edges metrics calculates error values in two areas related to typical artifacts of image enhancement algorithms: basic edges area and basic edges neighborhood. The metrics are illustrated with an application to image resampling and image deblurring but it is also applicable for image deringing and image denoising.