A Non-Local Means Filter for Removing the Poisson Noise
This addresses image denoising for applications like microscopy or astronomy where Poisson noise is common, but it appears incremental as it adapts an existing method.
The authors tackled image denoising under Poisson noise by proposing a modified Non-Local Means filter, demonstrating theoretical convergence at the optimal rate and showing competitive performance in simulations.
A new image denoising algorithm to deal with the Poisson noise model is given, which is based on the idea of Non-Local Mean. By using the "Oracle" concept, we establish a theorem to show that the Non-Local Means Filter can effectively deal with Poisson noise with some modification. Under the theoretical result, we construct our new algorithm called Non-Local Means Poisson Filter and demonstrate in theory that the filter converges at the usual optimal rate. The filter is as simple as the classic Non-Local Means and the simulation results show that our filter is very competitive.