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基于多曝光显微镜图像融合的细节增强算法。

Multi-exposure microscopic image fusion-based detail enhancement algorithm.

机构信息

Chandigarh Engineering College, Landran, Mohali, India.

Instituto de Optica (CSIC), Serrano 121, Madrid, Spain.

出版信息

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.

摘要

传统显微镜成像技术无法获取具有复杂二氧化硅细胞壁和多尺度图案的硅藻物种的完整动态范围。为了从硅藻中提取细节,使用显微镜技术在不同的曝光设置下捕获多曝光图像。最近的一项创新表明,图像融合克服了标准数码相机的局限性,可以从使用显微镜成像技术拍摄的高动态范围场景或标本中捕捉细节。在本文中,我们提出了一种基于细胞区域敏感曝光融合(CS-EF)的方法,以生成可以直接在常规显示设备上呈现的良好曝光融合图像。目标是保留 3D 透明硅藻壳中光照不良和过亮区域的细节。通过考虑局部信息度量,可以在输入曝光中选择曝光良好的区域,从而实现上述目标。此外,引入了一种改进的直方图均衡化方法,以在融合之前提高输入多曝光图像的均匀性。对所提出的融合结果进行定量和定性评估,结果表明其性能优于几种最先进的算法,这证明了该方法的有效性。

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