A new algorithm for object-oriented multi-scale high resolution remote sensing image segmentation
The rich spatial structure information and geographic information in a high-resolution remote sensing image are need to be extracted in different scales. However, the traditional image segmentation methods based on pixels spectral characteristics and singlescale image information extraction methods have obvious flaws in this respect In order to utilize the rich scale-dependent information contained in high resolution remote sensing images, the geo-science applications of remote sensing image and geographical information extraction must be carried out under multi-scale condition. Region-based object-oriented image analysis method provides a new idea for highresolution remote sensing image information extraction .The key issue is to realize multi-scale high resolution remote sensing image segmentation. In this paper, an object oriented multi-scale image segmentation method is introduced based on minimum heterogeneity criterion of neighbouring region growing. Segmentation results show that this method can easily adapt its scale parameter to different scale image analysis tasks and any chosen scale object-extraction of interest In a word, it can provide enormous object characteristics for further object-oriented processing or analysis.
high-resolution remote sensing image multi-scale segmentation ground object image region
An yong He guo-jin
Center for Earth Observation and Digital Earth Chinese Academy of Sciences Beijing, China
国际会议
2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)
上海
英文
1625-1628
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）