4.5 Article

Optical image fusion using support value transform (SVT) and curvelets

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OPTIK
卷 126, 期 18, 页码 1672-1675

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ELSEVIER GMBH, URBAN & FISCHER VERLAG
DOI: 10.1016/j.ijleo.2015.04.057

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Image fusion; LS-SVM (least square support vector machine); Support value transform (SVT) ridgelets; Curvelets

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In this paper, we introduce a new method based on a support value transform (SVT) and curvelet transform, which represents edges better than wavelets. Since edges play a fundamental role in image representation, one effective means to enhance spatial resolution is to enhance the edges. In this method the image is decomposed by support value filter. Then curvelet transform is used to combine decomposed planes for getting better edge quality. (C) 2015 Elsevier GmbH. All rights reserved.

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