摘要
二维熵的图像分割方法是一种常用的阈值分割技术,适合于对象和背景占据二维直方图绝大部分区域的图像分割,但该方法忽略了边界区域的信息对分割结果的影响。为保留图像的边界信息,对直方图中均值的选取进行了改进,应用了9种不同形状的模板,对每个像素点求均值和方差,选取方差最小的模板对应的均值构造二维直方图。实验结果表明,对于边界区域的信息量较大的图像,该方法的分割效果比较理想,并且也有良好的去噪效果。
2-D entropic thresholding method is a common image segmentation technology,it is suitable for the image segmentation of the object and background occupying the vast majority region of 2-D histogram,but this approach neglects the information of edge regions to the results of the segmentation.To preserve the image of the edge regions,this paper improves the select method of the mean of the histogram,uses different shape templates,achieves mean and variance of each pixel point, selects the mean of smallest variance template to struct two-dimensional histogram.Experimental results show that this method can obtain better segmentation results and denoising effect.
出处
《计算机工程与应用》
CSCD
北大核心
2009年第13期182-185,共4页
Computer Engineering and Applications
基金
国家自然科学基金No.60572133~~
关键词
二维熵法
最小方差
图像分割
直方图
2-D entropic method
the minimum variance
image segmentation
histogram
