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用于扩展景深的复小波:一种多通道显微镜图像融合的新方法。

Complex wavelets for extended depth-of-field: a new method for the fusion of multichannel microscopy images.

作者信息

Forster Brigitte, Van De Ville Dimitri, Berent Jesse, Sage Daniel, Unser Michael

机构信息

Swiss Federal Institute of Technology Lausanne (EPFL), Biomedical Imaging Group, LIB Bât. BM, CH-1015 Lausanne, Switzerland.

出版信息

Microsc Res Tech. 2004 Sep;65(1-2):33-42. doi: 10.1002/jemt.20092.

Abstract

Microscopy imaging often suffers from limited depth-of-field. However, the specimen can be "optically sectioned" by moving the object along the optical axis. Then different areas appear in focus in different images. Extended depth-of-field is a fusion algorithm that combines those images into one single sharp composite. One promising method is based on the wavelet transform. Here, we show how the wavelet-based image fusion technique can be improved and easily extended to multichannel data. First, we propose the use of complex-valued wavelet bases, which seem to outperform traditional real-valued wavelet transforms. Second, we introduce a way to apply this technique for multichannel images that suppresses artifacts and does not introduce false colors, an important requirement for multichannel optical microscopy imaging. We evaluate our method on simulated image stacks and give results relevant to biological imaging.

摘要

显微镜成像常常受到景深有限的困扰。然而,可以通过沿光轴移动物体对标本进行“光学切片”。然后,不同区域会在不同图像中聚焦。扩展景深是一种将这些图像融合成一张清晰合成图像的算法。一种很有前景的方法是基于小波变换。在这里,我们展示了基于小波的图像融合技术如何得到改进并轻松扩展到多通道数据。首先,我们建议使用复值小波基,它似乎比传统的实值小波变换表现更优。其次,我们介绍一种将此技术应用于多通道图像的方法,该方法能抑制伪像且不引入伪色,这是多通道光学显微镜成像的一项重要要求。我们在模拟图像堆栈上评估了我们的方法,并给出了与生物成像相关的结果。

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