An ImageJ plugin for image fusion based on edge-preserving filtering

Harbinder Singh; Manuel G. Forero; Nuray Ağaoğlu; Gloria Bueno; Oscar Deniz; Gabriel Cristobal

doi:10.1117/12.3017408

18 June 2024 An ImageJ plugin for image fusion based on edge-preserving filtering

Harbinder Singh, Manuel G. Forero, Nuray Ağaoğlu, Gloria Bueno, Oscar Deniz, Gabriel Cristobal

Proceedings Volume 12998, Optics, Photonics, and Digital Technologies for Imaging Applications VIII; 129980Q (2024) https://doi.org/10.1117/12.3017408
Event: SPIE Photonics Europe, 2024, Strasbourg, France

Abstract

A novel ImageJ plugin is designed to extend the depth-of-field (DoF) by seamlessly fusing a series of multi-focus images, allowing for in-depth analysis. Moreover, it has been tested on multi-exposure image stacks, demonstrating its adeptness in preserving intricate details within both poorly and brightly illuminated regions of 3-D specimens. The significance of this capability becomes particularly apparent when dealing with images that exhibit a limited DoF and varying exposure settings under low signal-to-noise ratio conditions. The plugin’s effectiveness has been thoroughly validated through the processing and analysis of numerous image stacks featuring diverse diatom and cyanobacteria species. The proposed methodology incorporates a two-scale decomposition (TSD) scheme, complemented by the refinement of weight maps using edge-preserving filtering (EPF). This dual approach ensures the preservation of fine details in the fused image while simultaneously minimizing noise. Such innovations make this plugin a valuable tool for researchers and analysts working with complex image datasets.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Harbinder Singh, Manuel G. Forero, Nuray Ağaoğlu, Gloria Bueno, Oscar Deniz, and Gabriel Cristobal "An ImageJ plugin for image fusion based on edge-preserving filtering", Proc. SPIE 12998, Optics, Photonics, and Digital Technologies for Imaging Applications VIII, 129980Q (18 June 2024); https://doi.org/10.1117/12.3017408

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