分形高斯噪声fgn是分形布朗运动的增量过程，广泛应用于自相似过程的建模分析。
Fractional Gaussian Noise (FGN) is the increment process of fractional Brownian motion, they are widely used in modelling self-similar process.
提出了一种针对加性白高斯噪声(AWGN)的改进分形图像去噪方法。
An improved fractal image denoising algorithm for removing additive white Gaussian noise (AWGN) was presented by adopting quadratic gray-level function.
模拟实验结果表明，该方法不仅具有高的分辨率，而且能有效地抑制分形差分高斯噪声的影响。
It is demonstrated by simulations that the new approach has high resolution and can suppress the effect of fractionally differenced Gaussian noise.
模拟实验结果表明，该方法不仅具有高的分辨率，而且能有效地抑制分形差分高斯噪声的影响。
It is demonstrated by simulations that the new approach has high resolution and can suppress the effect of fractionally differenced Gaussian noise.
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