74812 20190819101354.0 doi 10.1109/JSTSP.2017.2747126 sideral 101173 ART-2017-101173 eng Wu, Gaochang Light field image processing: an overview 2017 Access copy available to the general public Unrestricted Light field imaging has emerged as a technology allowing to capture richer visual information from our world. As opposed to traditional photography, which captures a 2D projection of the light in the scene integrating the angular domain, light fields collect radiance from rays in all directions, demultiplexing the angular information lost in conventional photography. On the one hand, this higher dimensional representation of visual data offers powerful capabilities for scene understanding, and substantially improves the performance of traditional computer vision problems such as depth sensing, post-capture refocusing, segmentation, video stabilization, material classification, etc. On the other hand, the high-dimensionality of light fields also brings up new challenges in terms of data capture, data compression, content editing, and display. Taking these two elements together, research in light field image processing has become increasingly popular in the computer vision, computer graphics, and signal processing communities. In this paper, we present a comprehensive overview and discussion of research in this field over the past 20 years. We focus on all aspects of light field image processing, including basic light field representation and theory, acquisition, super-resolution, depth estimation, compression, editing, processing algorithms for light field display, and computer vision applications of light field data. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 682080-CHAMELEON info:eu-repo/grantAgreement/EC/H2020/682080/EU/Intuitive editing of visual appearance from real-world datasets/CHAMELEON info:eu-repo/semantics/openAccess by-nc-nd http://creativecommons.org/licenses/by-nc-nd/3.0/es/ 4.361 2017 ENGINEERING, ELECTRICAL & ELECTRONIC 30 / 260 = 0.115 2017 Q1 T1 1.331 2017 Signal Processing 2017 Q1 Electrical and Electronic Engineering 2017 Q1 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion (orcid)0000-0003-0060-7278 Masia, Belen Universidad de Zaragoza (orcid)0000-0001-9000-0466 Jarabo, Adrian Zhang, Yuchen Wang, Liangyong Dai, Qionghai Chai, Tianyou Liu, Yebin 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 11, 7 (2017), 926-954 IEEE Journal of Selected Topics in Signal Processing IEEE Journal of Selected Topics in Signal Processing 1932-4553 6244239 http://zaguan.unizar.es/record/74812/files/texto_completo.pdf Postprint 139629 http://zaguan.unizar.es/record/74812/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:74812 articulos driver 2019-08-19-09:52:00 ARTICLE