NDLI: Visible and IR Data Fusion Technique Using the Contourlet Transform

Content Provider	IEEE Xplore Digital Library
Author	Ibrahim, S. Wirth, M.
Copyright Year	2009
Abstract	In the last few years image fusion has gained considerable attention, where it can provide remarkable outputs for many image applications (\emph{i.e.}, detection of hidden objects). Images with different specifications (resolution, spectral, and spatial) can be fused to produce an output image that combines the best features of all input images. The quality of the output image varies based on the application. In this paper, a new region-based image fusion technique using the Contourlet Transform (CT) is proposed. The presented fusion approach combines the visual information from a visual colored image, and some information about the hidden objects from an IR image. The fused output image is better for human and machine interpretation, where it preserves the original chromaticity of the visual input image. The input images are segmented into small regions more suitable for the proposed algorithm. The segmentation process is performed in the frequency domain. The presented region-based fusion approach is more robust than the traditional pixel-based techniques, where it reduces: the blurring effects, sensitivity to the misregistration problem, and noise effects in the input images. Experimental results demonstrate the capability of the presented fusion technique in detecting hidden weapons and objects. Moreover, the algorithm preserves very high percentage of the input image's spectral components.
Starting Page	42
Ending Page	47
File Size	1952171
Page Count	6
File Format	PDF
ISBN	9781424453344
DOI	10.1109/CSE.2009.228
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-29
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image resolution Hidden Weapons Humans Contourlet Transform Region-based Fusion Frequency domain analysis Image segmentation Computed tomography Object detection Noise robustness Spatial resolution Image fusion Pixel
Content Type	Text
Resource Type	Article

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