Poissonian and Gaussian noise is main source which affects the image quality captured by new generation of charge-coupled device. Lots of research interests have been paid on the noise suppression, but these works concentrated on the pure Poissonian or Gaussian noise. The proper noise model will improve the performance of noise removing. As noise and signal would be separated efficiently in sparse domain, the denoising performance will be improved if non-local repetitive structure is employed into denoising algorithm based on sparse coding. In this paper we propose a method for Poisson-Gaussian mixed noise reduction by exploiting the sparsity of signal over redundant dictionary and the self-similarity of imagery. Experiments are carried to demonstrate the efficiency and performance of our method over the state-of-art denoising method on a large number of imagerys.