Multi-channel and single-channel image denoising are on two important development fronts. Integrating multi-channel and single-channel image denoisers for further improvement is a valuable research direction. A natural assumption is that using more useful information is helpful to the output results. In this paper, a novel multi-channel and single-channel fusion paradigm (MSF) is proposed. The proposed MSF works by fusing the estimates of a multi-channel image denoiser and a single-channel image denoiser. The performance of recent multi-channel image denoising methods involved in the proposed MSF can be further improved at low additional time-consuming cost. Specifically, the validity principle of the proposed MSF is that the fused single-channel image denoiser can produce auxiliary estimate for the involved multi-channel image denoiser in a designed underdetermined transform domain. Based on the underdetermined transformation, we create a corresponding orthogonal transformation for fusion and better restore the multi-channel images. The quantitative and visual comparison results demonstrate that the proposed MSF can be effectively applied to several state-of-the-art multi-channel image denoising methods.

多通道和单通道图像去噪处于两个重要的发展前沿。集成多通道和单通道图像降噪器以进一步改进是一个有价值的研究方向。一个自然的假设是使用更多有用的信息有助于输出结果。在本文中，提出了一种新的多通道和单通道融合范式（MSF）。提出的 MSF 通过融合多通道图像降噪器和单通道图像降噪器的估计来工作。最近提出的 MSF 中涉及的多通道图像去噪方法的性能可以以较低的额外耗时成本进一步提高。具体来说，所提出的 MSF 的有效性原理是融合的单通道图像降噪器可以在设计的欠定变换域中为涉及的多通道图像降噪器产生辅助估计。基于欠定变换，我们创建了相应的正交变换进行融合，更好地恢复多通道图像。定量和视觉比较结果表明，所提出的 MSF 可以有效地应用于几种最先进的多通道图像去噪方法。