Blind and universal image denoising consists of using a unique model that denoises images with any level of noise. It is especially practical as noise levels do not need to be known when the model is developed or at test time. We propose a blind and universal deep learning image denoiser based on an optimal denoising solution, which we call fusion denoising. Our approach improves real-world grayscale additive image denoising. It also improves state-of-the-art color image denoising performance on every single noise level by an average of 0.1dB.