Complex wavelets for extended depth‐of‐field: A new method for the fusion of multichannel microscopy images

Abstract

KEY WORDSfocal range; optical microscopy; digital image processing; image fusion; complex wavelet transform 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. Microsc. Res. Tech. 65:33-42, 2004. © 2004 Wiley-Liss, Inc. INTRODUCTIONLimited depth-of-field is a common problem in biological imaging with conventional light microscopy. Often, the specimen's profile covers more than the attainable depth-of-field. Portions of the object's surface outside the optical plane appear defocused in the acquired image plane. This becomes worse as the magnification M increases because the numerical aperture NA increases, too:

Immunohistochemical localization of caffeine in young Camellia sinensis (L.) O. Kuntze (tea) leaves

“…Image stacks were converted to RGB and extended depth of field (EDF) easy (Forster et al 2004) was used. If needed the transform function was used to rotate images or vertically flip them.…”

A focus fusion framework with anisotropic depth map smoothing

“…Let us now compare our method with three publicly available approaches that represent different groups of techniques: As multiscale transformation-based method, we select the approach of Forster et al [5] that performs a complex wavelet decomposition. A representative of segmentation-based techniques is the method of Agarwala et al [13].…”

“…Here a first approach with application to focus fusion was published by Li et al [4]. Modifications and extensions have, for instance, been proposed by Forster et al [5] or Lewis et al [6]. In [7], Zhang and Blum present a generic framework for multiscale image fusion and compare different approaches.…”

Multimodality and Multiresolution Image Fusion

“…Based on anecdotal evidence, it appears less prone to artifacts like ringing effects. The latter are often perceived when image regions of high contrast are fused with the use of (standard, realvalued) wavelets (Forster et al, 2004). A theoretical disadvantage of the GP scheme is that it cannot boast of perfect reconstruction.…”