Variation-Based Approach to Restoring Blurred Images Corrupted by Poisson Noise
Guangxin Wang, Zhengming Wanag, Meihua Xie, Yarui Li · 2006
The restoration of blurred image with Poisson noise is investigated. According to the MAP estimation of the original image, we build a new criterion to measure the fidelity of the estimated image to the original image corrupted by Poisson noise, and construct a new variational model with a regularization term. The choice of the edge-preserving regularization function is addressed. To solve the variational model, we transform it into a nonlinear diffusion equation. Numerical experiments demonstrate that the proposed method results in high performance and preserves edges and reduces the Poisson noise effectively