关键词: 白高斯噪声, 噪声图像, 噪声估计, 统计假设测试

Abstract: Image noise estimation is a very important research topic in digital image processing. This paper presents a fast and reliable noise estimation algorithm for additive white Gaussian noise. The proposed algorithm provides a way to measure the degree of image feature based on Statistical Hypothesis Tests（SHT）. The proposed algorithm distinguishes homogeneous blocks and non-homogeneous blocks by the degree of image feature. It sets the minimal variance of these homogeneous blocks as a reference variance. And then it finds more homogeneous blocks whose variances are similar to the reference variance and which not contain edge. The noise variance is estimated from these homogeneous blocks by a weighted averaging process according to the degree of image feature. Compared with the existing noise estimation methods, the proposed algorithm performs well in the estimation precision and suitable for the Gaussian noise-infected images.

Key words: white Gaussian noise, noisy image, noise estimation, statistical hypothesis tests