Abstract
A patch-based noise level estimation algorithm is proposed in this paper, with patches generated from a single noisy image. One can easily estimate the noise level from image patches using principal component analysis (PCA) if the image comprises only weak textured patches. The challenge for patch-based noise level estimation is how to select weak textured patches from a noisy image. As described in this paper, we propose a novel algorithm to select weak textured patches from a single noisy image based on the gradients of the patches and their statistics. Then we estimate the noise level from the selected weak textured patches using PCA. We demonstrate experimentally that the proposed noise level estimation algorithm outperforms the state-of-the-art algorithm.
Selected weak textured patches and noise level estimation result
1) Single Image:
2) Berkeley Segmentation Dataset:
Matlab Toolbox:
Matlab code
References:
- Noise Level Estimation Using Weak Textured Patches of a Single Noisy Image [pdf]
Xinhao Liu, Masayuki Tanaka and Masatoshi Okutomi
Proceedings of IEEE International Conference on Image Processing (ICIP2012), September, 2012
- Single-image Noise Level Estimation for Blind Denoising [pdf]
Xinhao Liu, Masayuki Tanaka and Masatoshi Okutomi
IEEE Transactions on Image Processing (TIP), Vol.22, No.12, pp.5226-5237, December, 2013