NDLI: Adaptive neural network non-uniformity correction based on edge detection

Content Provider	IEEE Xplore Digital Library
Author	Xiu Liu Zhaorong Lin Liguo Song Wen Gaojin Yong Liu
Copyright Year	2012
Description	Author affiliation: Beijing Institute of Space Mechanics & Electricity, China (Xiu Liu; Zhaorong Lin; Liguo Song; Wen Gaojin) \|\| Baicheng Ordnance Test Center of China, China (Yong Liu)
Abstract	The fixed pattern noise (FPN) of the infrared focal plane array severely limits the system performance, and the non-uniformity correction algorithm is a key technique of thermal imaging system. The scene-based non-uniformity correction algorithm does not require a shutter to block the field of view, but utilizes the scene information of image sequences to calculate the infrared focal plane array non-uniformity parameters. This paper introduces an improved neural network non-uniformity correction algorithm, which speeds up the convergence rate of the conventional neural network algorithm. The improved algorithm employs the edge detection method to overcome the ghosting artifacts generated by the conventional algorithm. In the test of infrared image sequences, the algorithm introduced in this paper is proved to be reasonable and effective‥
Starting Page	288
Ending Page	293
File Size	1126641
Page Count	6
File Format	PDF
ISBN	9781467309653
e-ISBN	9781467309646
DOI	10.1109/CISP.2012.6469876
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	scene-based non-uniformity correction infrared focal plane array Image edge detection Signal processing algorithms Imaging Artificial neural networks Image sequences edge detection neural network Convergence
Content Type	Text
Resource Type	Article

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