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Research Article

Efficient image fusion method using improved Bi-dimensional Empirical Mode Decomposition

Pages 44-72 | Received 18 Aug 2023, Accepted 07 Jan 2024, Published online: 25 Feb 2024
 

ABSTRACT

Several transformations are used in image fusion to extract the different image spatial details. In this paper, an improved version of the BEMD (Bi-dimensional Empirical Mode Decomposition) is proposed and is used to propose an image fusion method aiming to have the high spatial resolution of the panchromatic image PAN and the spectral resolution of the multispectral image MS in the same fused image. The proposed improved BEMD permits to avoid using injection models that are used in image fusion for preserving the spectral signatures in the fused image. Mainly, we propose a new 2D extrema points extraction for BEMD. One of the most important characteristics of the proposed BEMD components is that they are more faithful to the EMD components; their local behaviour being of pure oscillating 2D mono-components with zero mean values. Comparisons, among predecessor methods with qualitative evaluation and various spectral and spatial quantitative measures, show the effectiveness and efficiency of the proposed image fusion method. In addition, this fusion method is computationally fast and can be used to quickly merge a massive volume of data.

Disclosure statement

No potential conflict of interest was reported by the author(s).

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