关键词: 图像分割, 高强度高斯噪声, 最大类间方差法, 二维直方图, 平均灰度-局部方差

Abstract: In view of the obvious shortage of several segmentation methods, such as the gray-the average gray level 2D histogram method, the average gray level-gradient method and 2D histogram oblique segmentation, which are low region homogeneity, low region contrast, and cannot segment accurately enough under the influence of high intensity Gauss noise. This paper proposes a method of maximum between-cluster variance correlation of average gray level-local variance 2D histogram, which uses local variance that not only takes the discrete degree of each pixel point and the center of pixel points into consideration, but also decreases the influence affected by noise. This paper uses a fast recursion algorithm to reduce the amount of calculation. The experimental results show that the method is better than the gray-the average gray level method and the average gray level-gradient method, and has more accurate segmentation results, higher region contrast, region homogeneity, and better anti-noise property.

Key words: image segmentation, high intensity Gauss noise, maximum between-cluster variance, 2D histogram, average gray level-local variance