A Median Filter Method for Image Noise Variance Estimation
Zhijun Pei, Qingqiao Tong, Lina Wang, Jun Zhang · 2010
Image noise estimation is of crucial importance for the computer vision algorithm, for the algorithm parameter is always adjusted to account for the variations in noise level over the captured images. A median filter method is provided for the image noise variance estimation in the paper. The image was first processed with a group of high pass digital filters constructed by several finite difference operators with different orders. For each filtered image data, a variance was estimated. And the noise variance is approximated by the median of those estimated variances. In order to avoid outlier issues when there are left image details in the residue, variances are estimated from each filtered image data for several different inter-quartile ranges, then a median is taken. The supposed median filter approach to image noise estimation is simple and effective, which has been verified by the experiments.