低空林地航拍图像拼接的改进缝合线算法

Improved optimal seamless-line algorithm of aerial image mosaic in low altitude woodland

【目的】图像拼接效果的优劣主要取决于图像配准和图像融合两个步骤。图像配准误差导致的错切以及图像序列间的视差导致的鬼影、重影问题可通过图像融合算法减小或消除。目前图像融合算法中最佳缝合线算法的综合效果较好,但没有考虑到拼接图的正射效果,并且无人机低空飞行时树高相对飞行高度比值较大,这在获取正射影像时是不可忽略的干扰因素。传统的数字正射影像(DOM)是基于数字高程模型(DEM)对单张影像进行数字微分纠正进而拼接成整个区域的正射影像图。但是,地形高程数据和植物的高度数据获取困难,而恢复出来的地形和植物高度与实际数据存在误差,造成DOM在局部边缘出现扭曲、模糊问题。本文提出一种不需要DEM数据,仅用图像信息使拼接结果图保留正射投影的改进缝合线算法。【方法】首先对SURF特征检测、匹配与筛选,用RANSAC算法求得的单应性矩阵确定相邻图像重叠区域;然后基于重叠区中像素点位置与相邻两图像中心点位置的距离差可以反映正射效果的思想,将距离差引入能量函数,同时设计了动态权值参数用来平衡颜色、结构和距离三者的重要程度,利用动态规划思想搜索得到最佳缝合线;最后在缝合线两侧进行多频带融合生成类似正射影像的无缝拼接图。【结果】实验图像来源于不同样地、不同飞行高度,在相邻两幅图像以及同一条带航线图像上将本文的改进缝合线算法与其他3种缝合线算法以及Pix4D生成的数字正射影像进行对比。实验结果表明,本文提出的缝合线改进算法能保留正射投影,视觉效果优于现有的缝合线算法,在城镇建筑图像的实验中局部效果优于Pix4D。【结论】本文针对无人机低空林地航拍图像拼接重影问题和拼接结果由于视角不同而产生非正射影像区域的问题,实现了一种不需要DEM数据进行数字微分纠正但能生成类似正射影像效果的改进缝合线算法。实验结果显示,本文算法优于目前的最佳缝合线算法,能够保留正射投影,效果类似DOM,并且在保证物体边缘清晰方面优于目前商用软件生成的DOM。这有利于更准确地计算林地的郁闭度,估算林地植被覆盖面积,对跟踪识别地表动植物也具有一定的帮助。除林地图像之外,本方法也可以推广到其他需要保留正射投影的低空航拍拼接应用领域,如城镇航拍图像等。

[Objective] Whether image stitching algorithm is effective or not depends on image registration and image blending. In the stitching of forestry aerial images,misalignment caused by registration error and ghost caused by disparity could be diminished or eliminated. Optimal seamless-linealgorithm＇s general effect is better than other blending algorithm. But it doesn＇t involve orthographic effect into stitching result. When UAV flies in a very low altitude,the ratio of tree height to flight height is larger,which impedes to obtain orthographic panorama. To get orthophoto of image stitching,traditional methods always use DEM data to compute digital differential rectification. However,DEM data and plant height are variable and difficult to measure. Besides,the recovered terrain as well as plant height have error with ground truth,which leads DOM to generate distortion and obscure in some local areas.Therefore, we proposed a novel improved optimal seamless-line blending algorithm using image information instead of DEM data,which can reserve orthographic projection in the final panorama.[Method]Firstly,SURF was extracted,matched and filtered. RANSAC algorithm was used to compute homographic transform matrix in order to obtain the overlap area. Secondly,we constructed energy function,including distance difference between each pixel in overlap area and its image center,based on the ideology that distance difference can reflect the orthographic effective. Each item＇s dynamic parameter was set to weigh color,structure and distance. Dynamic programming was applied to seek optimal seamless-line. In the end,multi-band blending was used to generate seamless panorama. [Result]The image datasets used in experiment varied from land region and UAV altitude. The stitching result of two neighbor images and airline image series showed that our method can reserve orthographic projection whose visual effect was better than current optimal seamless-line algorithm. In the town panorama test,our method was better than DOM generated by Pix4 D in local regions. [Conclusion] We proposed a novel improved optimal seamless-line algorithm using image information instead of DEM data. The algorithm can diminish misalignment and ghost,and can reserve orthographic projection in the final panorama,whose visual effect is similar to DOM. Besides,the method does better in retaining sharp edge of object than DOM generated by commercial software. The method helps to compute forest canopy density as well as vegetation coverage area more accurately,thus contributes to tracking and recognizing animals and plants more precisely. In addition to forestry,the algorithm can be extended to other types of aerial images,such as town images,and orthographic projection should be reserved in the panorama.