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Multi-exposure microscopic image fusion-based detail enhancement algorithm

Authors: Harbinder Singh; Gabriel Cristobal; Gloria Bueno; Saul Blanco; Simrandeep Singh; P.N. Hrisheekesha; Nitin Mittal;

Multi-exposure microscopic image fusion-based detail enhancement algorithm

Abstract

Traditional microscope imaging techniques are unable to retrieve the complete dynamic range of a diatom species with complex silica-based cell walls and multi-scale patterns. In order to extract details from the diatom, multi-exposure images are captured at variable exposure settings using microscopy techniques. A recent innovation shows that image fusion overcomes the limitations of standard digital cameras to capture details from high dynamic range scene or specimen photographed using microscopy imaging techniques. In this paper, we present a cell-region sensitive exposure fusion (CS-EF) approach to produce well-exposed fused images that can be presented directly on conventional display devices. The ambition is to preserve details in poorly and brightly illuminated regions of 3-D transparent diatom shells. The aforesaid objective is achieved by taking into account local information measures, which select well-exposed regions across input exposures. In addition, a modified histogram equalization is introduced to improve uniformity of input multi-exposure image prior to fusion. Quantitative and qualitative assessment of proposed fusion results reveal better performance than several state-of-the-art algorithms that substantiate the method's validity.

Country
Spain
Keywords

Diatoms, 2203.04 Microscopia Electrónica, Microscopy, 3308.11 Control de la Contaminación del Agua, Entropy, Image Enhancement, Ecología. Medio ambiente, 2417.20 Taxonomía Vegetal, Image decomposition, Image fusion, Gene Fusion, Histogram equalization, 2417.07 Algología (Ficología), Algorithms

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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