An efficient parameter selection criterion for image denoising

The performance of most image denoising systems depends on some parameters which should be set carefully based on noise distribution and its variance. As in some applications noise characteristics are unknown, in this research, a criterion which its minimization leads to the best parameter set up is introduced. The proposed criterion is evaluated for the wavelet shrinkage image denoising algorithm using the cross validation procedure. The criterion is tested for some different values of thresholds, and the output leading to the minimum criterion value is selected as the final denoised output. The resulting outputs of our method and the previous threshold selection scheme for the wavelet shrinkage, i.e. the median absolute difference (MAD), are compared. The objective and subjective test results show the improved efficiency of the proposed denoising algorithm