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作 者:沈燕 何迪 刘畅[1] 邱钧[1] Shen Yan;He Di;Liu Chang;Qiu Jun(Institute of Applied Mathematics,Beijing Information Science and Technology University,Beijing 100101,China)
机构地区:[1]北京信息科技大学应用数学研究所,北京100101
出 处:《激光与光电子学进展》2024年第24期404-411,共8页Laser & Optoelectronics Progress
基 金:国家自然科学基金(62001036,61931003,62171044)。
摘 要:对光场数据进行视点和像点平面支集的同时扩展并保持较好的空角一致性,是光场数据扩展的难点之一。提出利用神经光场网络表示经双平面参数化的光线,通过生成原子光场数据中不存在的光线,对视点和像点平面支集实现扩展。统计扩展部分生成光线的误差,参照子光场重叠区域生成光线与原数据的误差,确定扩展部分生成效果好的数据占比,分析子光场重叠区域大小对扩展光场效果的影响。Blender模拟数据的实验结果表明,所提方法能够实现子光场视点和像点平面支集的同时扩展,并且极平面图像(EPI)显示,扩展部分能保持较好的空角一致性。当子光场数据重叠区域占比从42.9%提高到77.8%时,扩展区域生成效果好的数据占比由82.91%提升至84.68%。该分析在进行光场数据扩展时,对子光场数据的设计具有一定的指导意义。One of the difficulties in the expansion of light field data is to expand the viewpoint and image point plane support simultaneously and maintain a good space-angle consistency.In this paper,we propose to use the neural light field network to represent the rays parameterized by a biplane,generate the rays that do not exist in the atomic light field data,and extend the viewpoint and image plane branches.To gather statistics of extension part of the error of generated rays,we refer to the error between the generated rays and original data in the overlapping area of the sub-light field.It allows determining the proportion of data with good generation effect in the extended part.We analyze the influence of the size of the overlapping area of the sub-light field on the effect of the extended light field.Experimental results on Blender simulation data show that the proposed method can realize the simultaneous expansion of the sub-light field viewpoint and image plane branch,and the epipolar plane images(EPI)display extension part can maintain a good space-angle consistency.When the proportion of overlapping regions of sub-light field data increases from 42.9%to 77.8%,the proportion of data with good generation effect in extended regions increases from 82.91%to 84.68%.This analysis has certain guiding significance for the design of sub-light field data when expanding light field data.
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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