Abstract
We propose a simple method for estimating noise level from a single color image. In most image-denoising algorithms, an accurate noise-level estimate results in good denoising performance; however, it is difficult to estimate noise level from a single image because it is an ill-posed problem. We tackle this problem by using prior knowledge that textures are highly correlated between RGB channels and noise is uncorrelated to other signals. We also extended our method for RAW images because they are available in almost all digital cameras and often used in practical situations. Experiments show the high noise-estimation performance of our method in synthetic noisy images. We also applied our method to natural images including RAW images and achieved better noise-estimation performance than conventional methods.
Abstract (translated)
本文提出了一种从单色图像中估计噪声级的简单方法。在大多数图像去噪算法中，精确的噪声水平估计可以获得良好的去噪性能；然而，由于它是一个不适定问题，很难从单个图像中估计噪声水平。我们利用先前的知识来解决这个问题，即纹理在RGB通道之间高度相关，噪声与其他信号不相关。我们还扩展了原始图像的方法，因为它们几乎可以在所有数码相机中使用，并且经常用于实际情况。实验表明，该方法在合成噪声图像中具有较高的噪声估计性能。我们还将我们的方法应用于包括原始图像在内的自然图像，获得了比传统方法更好的噪声估计性能。
URL
https://arxiv.org/abs/1904.02566
