| 基于自适应全局阈值融合标记的遥感图像建筑群分割 |
| |
| 引用本文： | 李丽,柴文婷,梅树立.基于自适应全局阈值融合标记的遥感图像建筑群分割[J].农业机械学报,2013,44(7):222-228. |
| |
| 作者姓名： | 李丽 柴文婷 梅树立 |
| |
| 作者单位： | 中国农业大学信息与电气工程学院,北京,100083 |
| |
| 基金项目： | 国家自然科学基金资助项目（41171337）;现代农业产业技术体系建设专项基金资助项目(nycytx-30) |
| |
| 摘 要： | 针对分割遥感图像建筑群时,标记不完全所产生的过分割和欠分割并存问题,提出一种基于自适应全局阈值融合标记的图像分割算法.该算法根据建筑群的分布和纹理特点,利用小波变换提取图像梯度,通过形态学重构对梯度图像进行滤波；采用局部极小值法提取背景标记,并应用自适应全局阈值法提取建筑群标记.采用逻辑运算进行标记融合,用融合后的标记修改加权像素的Sobel梯度图实现精准分割.实验结果表明,该算法能够弥补形态学滤波梯度图的局部极值标记不足问题,抑制了建筑群的过分割和欠分割,准确地将建筑群从背景中提取出来,分割正确率达到90.7％.
|
| 关 键 词： | 遥感图像 建筑群 图像分割 形态学 融合标记 自适应全局阈值 |
Segmentation of Remote Sensing Images Based on Adaptive Global Threshold and Fused Markers |
| |
| Li Li,Chai Wenting and Mei Shuli.Segmentation of Remote Sensing Images Based on Adaptive Global Threshold and Fused Markers[J].Transactions of the Chinese Society of Agricultural Machinery,2013,44(7):222-228. |
| |
| Authors: | Li Li Chai Wenting and Mei Shuli |
| |
| Institution: | China Agricultural University;China Agricultural University;China Agricultural University |
| |
| Abstract: | Based on the method of adaptive global threshold and markers fusion, an algorithm was proposed in order to solve the problems of over-segmentation and the under-segmentation caused by incomplete marking, which might occur concurrently during the segmentation of remote sensing building images. First, the algorithm was used in wavelet transform to generate image gradient according to the distribution and texture characteristics of buildings, and the generated gradient image was filtered through morphological reconstruction. Then, the background markers were extracted by local minimum and the building makers by adaptive global threshold. After both markers were fused, they were used to modify the weighted pixel Sobel gradient image for accurate image segmentation. The experimental results demonstrated that the algorithm could make up for a lack of the local extreme marker, and significantly inhibited both over-segmentation and the under-segmentation. As a result, the segmentation accuracy reached to 90.7%. |
| |
| Keywords: | Remote sensing images Buildings Image segmentation Morphological reconstruction Fused marker Adaptive global threshold |
| 本文献已被 万方数据 等数据库收录！ |
| 点击此处可从《农业机械学报》浏览原始摘要信息 |
| 点击此处可从《农业机械学报》下载免费的PDF全文 |
|
