摘要
针对现有光场深度重建算法只能获取单一视角深度信息,三维建模应用受限的问题,提出一种大视野图像拼接算法。该算法基于三维光场重建的深度图像序列,采用双边滤波及插值算法对图像进行去除噪声,利用基于边缘曲率极值的角点检测算法,并通过最小曲率偏差的列间度量匹配实现了图像之间的精确配准,采用改进的加权平均方法对重叠区域进行融合操作,既保留图像细节又拓展图像视野。实验结果表明,该算法能够有效实现光场深度图像序列的平滑拼接,有利于形成大视野深度数据,为大场景的三维重建奠定了基础。
A new image stitching algorithm is proposed based on depth images series,to overcome the limit of fieldof-view of depth reconstruction from three-dimensional light field.At pre-processing stage,bilateral filter and interpolation is utilized to de-noise.A corner detection algorithm based on edge local-maximum curvature value,and a matching algorithm based on minimum curvature variance control are proposed.Improved weighted average method is adopted to complete image fusion,both retain image′s details and expand field-of-view.Experimental results show that the proposed system can easily obtain a complete depth image,which is helpful for threedimensional reconstruction of whole scene.
作者
王文锋
张焱鑫
陈瑜
丁伟利
Wang Wenfeng;Zhang Yanxin;Chen Yu;Ding Weili(Institute of Vehicles and Energy,Yanshan University,Qinhuangdao,Hebei 066004,China;Institute of Electrical Engineering,Yanshan University,Qinhuangdao,Hebei 066004 China)
出处
《光学学报》
EI
CAS
CSCD
北大核心
2018年第9期260-267,共8页
Acta Optica Sinica
基金
国家自然科学基金(51505414
61005034)
河北省自然科学基金(F2016203211)
燕山大学自主研究计划课题(15LGA014)
关键词
机器视觉
图像拼接
光场图像
深度重建
极平面图像自适应
machine vision
image stitching
light field images
depth reconstruction
adaptive epipolar plane image