Multi-exposure microscopic image fusion-based detail enhancement algorithm

Ultramicroscopy. 2022 Jun:236:113499. doi: 10.1016/j.ultramic.2022.113499. Epub 2022 Mar 12.

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.

Keywords: Entropy; Histogram equalization; Image decomposition; Image fusion.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Diatoms*
  • Gene Fusion
  • Image Enhancement* / methods
  • Microscopy