Patch based denoising methods, such as the NL-Means, have emerged recently as simple and efficient denoising methods. This paper provides a new insight on those methods by showing their connection with recent statistical aggregation techniques. Within this aggregation framework, we propose some novel patch based denoising methods. We provide some theoretical justification and then explain how to implement them with a Monte Carlo based algorithm.