针对图像中的高斯白噪声,提出了一种利用小波系数分布特征进行噪声估计的算法。根据小波系数的分布特点,利用广义高斯分布模型对小波系数进行拟合,并用广义高斯分布模型参数(尺度和形状参数)提出了一种有效的噪声方差估计算法。实验结果表明,提出的噪声方差估计算法能有效地估计噪声方差大小,同时估计的结果要好于其它相关的算法。这种噪声测量算法具有高精度性和快速性。
To estimate noise variance of Gaussian white noise, a new method by the character of wavelet coefficients distribution is proposed. The wavelet coefficients in each sub-band can be well modelized by a Generalized Gaussian Distribution (GGD) whose parameters (scale and shape parameters ) can be used to estimate noise variance. The simulation results show that the noise variance estimate method is efficient. It can obtain approximately optimal value, and need less computing time.