基于显著图的输电线路杆塔图像拼接方法  

Image mosaic approach of transmission tower based on saliency map

作　　者：张旭[1,2] 高佼[1,2] 王万国[1,2] 刘俍[1,2] 张晶晶[1,2] 

机构地区：[1]国网山东省电力公司电力科学研究院国家电网公司电力机器人技术实验室,济南250002 [2]山东鲁能智能技术有限公司,济南250101

出　　处：《计算机应用》2015年第4期1133-1136,共4页journal of Computer Applications

摘　　要：无人机拍摄的输电线路杆塔图像分辨率高且背景复杂,基于传统特征点的拼接算法在背景中检测出大量的特征点增加了图像匹配的时间,影响了杆塔的匹配精度。针对该问题提出了一种既稳定又具有较小时间开销的输电线路杆塔图像自动拼接方法,利用改进的显著性检测算法得到杆塔图像的显著图,将图像的前景与背景分离,减少了背景对图像中杆塔拼接效果的影响;并采用基于定向的加速分割检测特征(FAST)和旋转不变性的二进制鲁棒独立元素特征(BRIEF)描述子(ORB)特征点的图像匹配算法,以提高特征点提取和匹配的速率;最后利用多尺度融合策略得到最终的拼接结果。实验结果表明,所提方法具有较好的拼接效果和拼接效率。Images of transmission tower acquired by Unmanned Aerial Vehicle（ UAV） have high resolution and complex background, the traditional stitching algorithm using feature points can detect a large number of feature points from background which costs much time and affects the matching accuracy. For solving this problem, a new image mosaic algorithm with quick speed and strong robustness was proposed. To reduce the influence of the background, each image was first segmented into foreground and background based on a new implementation method of salient region detection. To improve the feature point extraction and reduce the computation complexity, transformation matrix was calculated and image registration was completed by ORB（ Oriented Features from Accelerated Segment Test（ FAST） and Rotated Binary Robust Independent Elementary Features（ BRIEF）） feature. Finally, the image mosaic was realized with image fusion method based on multi-scale analysis.The experimental results indicate that the proposed algorithm can complete image mosaic precisely and quickly with satisfactory mosaic effect.

关 键 词：无人机 图像拼接 显著性区域检测 显著图 ORB特征 图像匹配 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]