Simultaneous digital super-resolution and nonuniformity correction for infrared imaging systems

In this article, we present a novel algorithm to achieve simultaneous digital super-resolution and nonuniformity correction from a sequence of infrared images. We propose to use spatial regularization terms that exploit nonlocal means and the absence of spatial correlation between the scene and the...

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Bibliographic Details
Published in:Applied optics (2004) 2015-07, Vol.54 (21), p.6508-6515
Main Authors: Meza, Pablo, Machuca, Guillermo, Torres, Sergio, Martin, Cesar San, Vera, Esteban
Format: Article
Language:English
Subjects:
Algorithms
Digital imaging
Infrared imagery
Noise
Nonuniformity
Optimization
Strategy
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Summary:In this article, we present a novel algorithm to achieve simultaneous digital super-resolution and nonuniformity correction from a sequence of infrared images. We propose to use spatial regularization terms that exploit nonlocal means and the absence of spatial correlation between the scene and the nonuniformity noise sources. We derive an iterative optimization algorithm based on a gradient descent minimization strategy. Results from infrared image sequences corrupted with simulated and real fixed-pattern noise show a competitive performance compared with state-of-the-art methods. A qualitative analysis on the experimental results obtained with images from a variety of infrared cameras indicates that the proposed method provides super-resolution images with significantly less fixed-pattern noise.
ISSN:1559-128X
2155-3165
DOI:10.1364/AO.54.006508