A 2D bivariate EMD algorithm for image fusion

Foteini Agrafioti, Jiexin Gao, H. Mohammadzade, D. Hatzinakos
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引用次数: 5

Abstract

Although the benefits of the empirical mode decomposition, in analyzing stochastic signals have been reported, and the algorithm has been established for fusion applications, there is currently no solution to the problem of the simultaneous decomposition of 2D data. This paper proposes an extension of the bivariate EMD (BEMD) [1] algorithm for 2D sources, which retains spatial information while addressing the uniqueness problem of the intrinsic mode functions. The performance of the algorithm is tested on partially blurred and defocused images. The fused images are compared against 1D-BEMD solutions, to demonstrate increased visual quality of the result.
一种二维二元EMD图像融合算法
虽然经验模态分解在分析随机信号方面的优势已经被报道,并且该算法已经建立用于融合应用,但目前还没有解决二维数据同时分解的问题。本文提出了二维源的二元EMD (BEMD)[1]算法的扩展,在保留空间信息的同时解决了内禀模态函数的唯一性问题。在部分模糊和散焦图像上测试了算法的性能。将融合后的图像与1D-BEMD方案进行比较,以证明结果的视觉质量有所提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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