Title
Measuring the performance of super-resolution reconstruction algorithms
Author
Dijk, J.
Schutte, K.
van Eekeren, A.W.M.
Bijl, P.
Contributor
Holst, G.C. (editor)
Publication year
2012
Abstract
For many military operations situational awareness is of great importance. This situational awareness and related tasks such as Target Acquisition can be acquired using cameras, of which the resolution is an important characteristic. Super resolution reconstruction algorithms can be used to improve the effective sensor resolution. In order to judge these algorithms and the conditions under which they operate best, performance evaluation methods are necessary. This evaluation, however, is not straightforward for several reasons. First of all, frequency-based evaluation techniques alone will not provide a correct answer, due to the fact that they are unable to discriminate between structure-related and noise-related effects. Secondly, most super-resolution packages perform additional image enhancement techniques such as noise reduction and edge enhancement. As these algorithms improve the results they cannot be evaluated separately. Thirdly, a single high-resolution ground truth is rarely available. Therefore, evaluation of the differences in high resolution between the estimated high resolution image and its ground truth is not that straightforward. Fourth, different artifacts can occur due to super-resolution reconstruction, which are not known on forehand and hence are difficult to evaluate. In this paper we present a set of new evaluation techniques to assess super-resolution reconstruction algorithms. Some of these evaluation techniques are derived from processing on dedicated (synthetic) imagery. Other evaluation techniques can be evaluated on both synthetic and natural images (real camera data). The result is a balanced set of evaluation algorithms that can be used to assess the performance of super-resolution reconstruction algorithms.
Subject
Signal-to-noise ratio
MTF enhancements
Enhancement techniques
Evaluation algorithm
Ground truth
High resolution
Natural images
Performance evaluation
Sensor resolution
Situational awareness
Target acquisition
Imaging systems
Infrared imaging
Military operations
Algorithms
Defence Research
Defence, Safety and Security
Physics & Electronics Human
II - Intelligent Imaging PCS - Perceptual and Cognitive Systems
TS - Technical Sciences BSS - Behavioural and Societal Sciences
To reference this document use:
http://resolver.tudelft.nl/uuid:97bf16d4-4100-4126-a468-58abde2db888
DOI
https://doi.org/10.1117/12.919225
TNO identifier
462335
Publisher
SPIE, Bellingham, WA
Source
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXIII, 24 April 2012, Baltimore, MD, USA
Series
Proceedings of SPIE
Document type
conference paper