自然场景统计噪声估计

Praful Gupta, C. Bampis, Yize Jin, A. Bovik
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引用次数: 14

摘要

我们研究了自然图像在dct滤波域的分归一化带通响应的尺度不变性质。我们发现原始自然图像的归一化DCT滤波响应的方差是尺度不变的。这种尺度不变性在存在噪声的情况下不成立,因此可以用来设计一种有效的盲图像噪声估计器。提出的噪声估计方法优于其他基于统计的方法,特别是在高噪声水平下,并与基于补丁和基于滤波器的方法竞争。此外,新的方差估计方法在非高斯噪声的情况下也很有效。提出的算法的研究代码可以在https://github.com/guptapraful/Noise估计中找到。
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Natural Scene Statistics for Noise Estimation
We investigate the scale-invariant properties of divisively normalized bandpass responses of natural images in the DCT-filtered domain. We found that the variance of the normalized DCT filtered responses of a pristine natural image is scale invariant. This scale invariance property does not hold in the presence of noise and thus it can be used to devise an efficient blind image noise estimator. The proposed noise estimation approach outperforms other statistics-based methods especially for higher noise levels and competes well with patch-based and filter-based approaches. Moreover, the new variance estimation approach is also effective in the case of non-Gaussian noise. The research code of the proposed algorithm can be found at https://github.com/guptapraful/Noise Estimation.
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