CAJ | 학술논문

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。
제출일충기우도상분할적조성방차량보고계산법。제일보，대함유조성적도상진행평활，재이용통계구역귀병산법대도상진행분할，병계산매개구역적방차，근거통계규률선택괄당적구역고계도상중조성방차。제이보，이용초시고계적방차，수정평활려파、도상분할급조성고계적삼수，진행신일륜적평활、분할화방차고계，득출경위준학적고계결과。재대량도상화불동조성정황하적실험결과표명，해산법가이쾌속、준학지고계도상중조성방차。
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.