计算机工程Issue(5)：234-237,242,5.DOI:10.3969/j.issn.1000-3428.2014.05.048
基于三维直方图修正和灰度熵分解的图像分割
Image Segmentation Based on Three-dimensional Histogram Correction and Gray Entropy Decomposition
摘要
Abstract
Aiming at the problem of inaccurating image segmentation caused by image noise and the common threshold selection methods which only rely on the probabilistic information from the image histogram is without directly thinking of the uniformity of the image inter-class gray distribution, a threshold selection algorithm based on a three-dimensional histogram correction and gray entropy de-composition is proposed. It analyzes the influence of image noise to the gray of pixel’s neighborhood region, and reduces the noise interference by modifying the three-dimensional histogram. A formula of threshold selection based on three-dimensional gray entropy is presented, and the dimension of gray entropy is decomposed to one dimension, which makes the computation complexity reduced from O(L3) to O(L). Experimental results show that, compared with two-dimensional maximum entropy algorithm based on oblique segmen-tation, two-dimensional cross entropy algorithm based on recursion and three-dimensional Otsu algorithm based on dimension reduction, the presented algorithm has better anti-noise performance, visual quality and the operation time is reduced by about 10%at least.关键词
图像分割/阈值选取/图像噪声/三维直方图/分解处理/灰度熵Key words
image segmentation/threshold selection/image noise/three-dimensional histogram/decomposition processing/gray entropy分类
信息技术与安全科学引用本文复制引用
张书真..基于三维直方图修正和灰度熵分解的图像分割[J].计算机工程,2014,(5):234-237,242,5.基金项目
国家自然科学基金资助项目(61262032)；湖南省教育厅科学研究基金资助项目(12C0314)。 （61262032）
