A dense light field reconstruction algorithm for four-dimensional optical flow constraint equation

• Published in: Pattern recognition Vol. 134; p. 109101
• Main Authors: Liu, Jian, Song, Na, Xia, Zhengde, Liu, Bin, Pan, Jinxiao, Ghaffar, Abdul, Ren, Jianbin, Yang, Ming
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.02.2023
• Subjects: A dense reconstruction; Light field; Optical flow; A dense reconstruction; Optical flow; Light field
• ISSN: 0031-3203; 1873-5142
• DOI: 10.1016/j.patcog.2022.109101

•The establishment of a new mathematical model to realize dense light field reconstruction.•The innovative application of optical flow method.•Simple algorithm structure and relatively easy to implement.•Algorithm strong adaptability, good dense reconstruction was completed. Dense light field sampling is an important basis for refocusing, depth estimation and 3-D imaging. It is difficult to obtain high resolution dense light field with a large-scale camera array and expensive equipment. At the same time, the current storage devices and transmission bandwidth also limit this technology's post-processing and application. In order to effectively reconstruct the angle domain of the light field based on the sparse light field data, this paper analyzes the correlation and constraint relationship between the optical flow field and the motion field of multi-view images in the same scene, extends the traditional optical flow constraint equation of two-dimensional imaging to the optical flow constraint equation of four-dimensional light field, and establishes an effective mathematical model. The coordinate position of the original pixel in the new angle image is determined by coordinate search, and its intensity is reconstructed. The experimental results of multi-scene dense reconstruction show that the proposed method can reconstruct the texture, shadow and color information in the light field of a long-baseline scene with high quality. The quantitative evaluation results show that the algorithm can be applied to dense light field reconstruction of complex scenes. The algorithm in this paper is only suitable for the case of optical flow constraint in a linear light field, and the follow-up research will focus on the case of nonlinear optical flow constraint.