Microscopy imaging often suffers from limited depth-of-focus. However, the specimen can be “optically sectioned” by moving the object along the optical axis; different areas appear in focus in different images. Extended depth-of-focus is a fusion algorithm that combines those images into one single sharp composite. One promising method is based on the wavelet transform. In this paper, we show how the wavelet-based image fusion technique can be improved and easily extended to multi-channel 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 multi-channel images that suppresses artifacts and does not introduce false colors, an important requirement for multi-channel fluorescence microscopy imaging. We evaluate our method on simulated image stacks and give results relevant to biological imaging.