本文選題：種子點自動獲取 + 梯度值�。� 參考：《科學(xué)技術(shù)與工程》2017年33期

【摘要】：鑒于區(qū)域生長存在需提供種子點及易過生長的缺陷,改進了區(qū)域生長算法對高分辨率遙感影像進行道路精確提取。首先利用格網(wǎng)對原始影像進行劃分,將在道路灰度范圍內(nèi)的外邊緣格網(wǎng)以同質(zhì)性指標依次排序作為候選種子點;將滿足道路連續(xù)性和一致性要求的路徑格網(wǎng)起始點作為種子點;并通過道路指數(shù)加以驗證得到最終種子點,以此避免盲目選擇種子點的不足。其次在引入梯度值進行道路生長后,以二值化的彩色分量與生長結(jié)果進行信息融合方式來優(yōu)化算法,達到緩解過生長的目的。實驗結(jié)果表明算法是合理有效的,能夠較為精確地提取出道路區(qū)。
[Abstract]:In view of the defects of region growth which need to provide seed points and be easy to grow, an improved region growth algorithm is proposed for accurate road extraction from high-resolution remote sensing images. Firstly, the original image is divided by grid, and the outer edge grid in the range of road grayscale is ranked as the candidate seed point by homogeneity index, and the starting point of the path grid that meets the requirements of road continuity and consistency is taken as the seed point. Finally, the final seed points are obtained by road index, so as to avoid the shortage of blind selection of seed points. Secondly, after introducing gradient value for road growth, the information fusion of binary color component and growth result is used to optimize the algorithm to alleviate overgrowth. The experimental results show that the algorithm is reasonable and effective, and can extract the road area accurately.
【作者單位】： 中國地質(zhì)大學(xué)(武漢)信息工程學(xué)院;河南財經(jīng)政法大學(xué)資源與環(huán)境學(xué)院;
【基金】：國家863計劃資助項目(2007AA092102) 高分辨率對地觀測重大專項(07-Y30A05-9001-12/13)資助
【分類號】：TP751

【相似文獻】

相關(guān)期刊論文 前1條

1 葉勤;張小虎;王棟;;一種基于區(qū)域生長與空間形狀約束的高分辨率遙感圖像道路提取方法[J];遙感信息;2010年02期

，

本文編號：2064605