CAJ | 학술논문

在数字图像处理中，噪声方差估计是一个重要的研究课题。提出一种针对加性高斯噪声的噪声方差估计方法。利用一种基于统计假设测试的方法来度量图像结构特征度，基于图像结构特征度找出平滑子块和非平滑子块（含有边缘或纹理子块）；以平滑子块中的最小方差为参考方差，选择出方差与参考方差相差在一定范围内且不含边缘的所有子块；从选出的子块中求以图像结构特征度为权重的方差平均值作为噪声方差估计值。相比于现有的噪声估计方法，该方法具有非常高的估计精度，适合感染高斯噪声的各种图像。
재수자도상처리중，조성방차고계시일개중요적연구과제。제출일충침대가성고사조성적조성방차고계방법。이용일충기우통계가설측시적방법래도량도상결구특정도，기우도상결구특정도조출평활자괴화비평활자괴（함유변연혹문리자괴）；이평활자괴중적최소방차위삼고방차，선택출방차여삼고방차상차재일정범위내차불함변연적소유자괴；종선출적자괴중구이도상결구특정도위권중적방차평균치작위조성방차고계치。상비우현유적조성고계방법，해방법구유비상고적고계정도，괄합감염고사조성적각충도상。
Image noise estimation is a very important research topic in digital image processing. This paper presents a fast and reliable noise estimation algorithm for additive white Gaussian noise. The proposed algorithm provides a way to measure the degree of image feature based on Statistical Hypothesis Tests(SHT). The proposed algorithm distinguishes homogeneous blocks and non-homogeneous blocks by the degree of image feature. It sets the minimal variance of these homogeneous blocks as a reference variance. And then it finds more homogeneous blocks whose variances are similar to the reference variance and which not contain edge. The noise variance is estimated from these homogeneous blocks by a weighted averaging process according to the degree of image feature. Compared with the existing noise estimation methods, the proposed algo-rithm performs well in the estimation precision and suitable for the Gaussian noise-infected images.