CAJ | 학술논문

利用遥感图像提取道路边缘信息可以简化常规城市道路的测绘工作。根据一般道路在图像上的影像特征对图像进行模型化处理,提出了基于双阈值的序贯相似性检测算法( sequential similarity detection algorithm,SSDA)的模板匹配算法,并在该算法的基础上,提出了一个基于减小增长误差的算子,用以减少由于样本数过多而产生的增长误差。与其他算法相比,该算法能够更有效地获取道路边缘信息,在准确提取路面边缘信息的同时,能对预处理中难以完全提取的路面部分进行修复,减少处理过程,从而提高处理效率。
이용요감도상제취도로변연신식가이간화상규성시도로적측회공작。근거일반도로재도상상적영상특정대도상진행모형화처리,제출료기우쌍역치적서관상사성검측산법( sequential similarity detection algorithm,SSDA)적모판필배산법,병재해산법적기출상,제출료일개기우감소증장오차적산자,용이감소유우양본수과다이산생적증장오차。여기타산법상비,해산법능구경유효지획취도로변연신식,재준학제취로면변연신식적동시,능대예처리중난이완전제취적로면부분진행수복,감소처리과정,종이제고처리효솔。
Extracting road edge information from remote sensing image can simplify the conventional urban road mapping work. Based on the general road image features, this paper proposes a dual-threshold SSDA ( sequential similarity detection algorithm) template matching method in an image processing model. And on the basis of the general SSDA, another algorithm is presented to reduce the excessive number of samples responsible for the error growth. Compared with other algorithms, this algorithm can more effectively access the road edge information extraction. As for some parts of the road which cannot be completely extracted through pretreatment process, the detection results can be corrected to reduce treatment, and hence the processing efficiency will be improved.