基于图像分割的噪声方差估计
Noise variance estimation based on image segmentation
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摘要: 提出一种基于图像分割的噪声方差两步估计算法.第一步,对含有噪声的图像进行平滑,再利用统计区域归并算法对图像进行分割,并计算每个区域的方差,根据统计规律选择适当的区域估计图像中噪声方差.第二步,利用初始估计的方差,修正平滑滤波、图像分割及噪声估计的参数,进行新一轮的平滑、分割和方差估计,得出更为准确的估计结果.在大量图像和不同噪声情况下的实验结果表明,该算法可以快速、准确地估计图像中噪声方差.Abstract: A new two-step noise variance estimation algorithm was proposed based on image segmentation. In the first step, a noisy image was smoothed and was segmented by the statistical region merge (SRM) algorithm, then the variance of each region was computed, and some regions were selected based on the statistical rule to estimate the noise variance. In the second step, the parame-ters of filtering, segmentation and estimation were revised according to the estimated noise variance, and a new cycle of image filte-ring, segmentation and estimation was performed to obtain more accurate estimation. Experimental results on large numbers of images and various noises show that the proposed algorithm can estimate the noise variance quickly and accurately.