直线截距直方图城区遥感图像多阈值分割

Multi-level thresholding for remote sensing image of urban area based on line intercept histogram

阈值分割简单有效,但现有的单阈值方法对城区图像分割效果不佳,难以取得令人满意的结果。为了快速准确地对城区遥感图像进行分割,本文提出了基于直线截距直方图倒数灰度熵和人工蜂群优化(artificial bee colony optimization,ABC)的多阈值分割方法。首先,给出直线截距直方图的定义并建立城区遥感图像的直线截距直方图;然后,计算该直方图倒数灰度熵的大小,推导出其单阈值选取公式;最后,将其推广到多阈值选取,并利用人工蜂群优化算法,对多个阈值进行快速精确地寻优,以此最终实现城区遥感图像的多阈值分割。实验结果表明,该方法所分割的图像中多目标的形状、边缘更为准确,纹理及细节特征更加清晰,且所需运行时间仅为同类多阈值分割方法的25%,是一种行之有效的城区遥感图像分割方法。

Threshold segmentation is a kind of simple and effective method,however,the existing single-threshold method is hard to realize satisfactory effect in segmenting the images of urban area.In order to segment the remote sensing images of urban area quickly and accurately,a multi-threshold segmentation method based on straight-line intercept histogram,reciprocal grayscale entropy and Artificial Bee Colony(ABC)Optimization was proposed in the paper.Firstly,the straight-line intercept histogram was defined and the straight-line intercept histogram of the urban remote sensing image was established;then the value of the reciprocal grayscale entropy of the histogram was calculated and the single-threshold selection formula was deduced;finally,the application was popularized to multi-threshold selection,ABC Optimization algorithm was utilized for precise optimization of many thresholds,so as to finally realize the multithreshold segmentation of urban remote sensing images.A large number of experiments show that,the multi-object shape and edge in the images segmented by the method are more accurate,the textures and details are more explicit,in addition,its running time is only25%of other similar multi-threshold segmentation methods.This is a kind of effective method for segmenting the remote sensing images of urban area.