2018 · 18 citations · 26 references
ComputingVision ScienceComputer VisionMachine VisionRenderingDepth EstimationImage SynthesisCost Function ModelingDepth Map EstimationDepth Map ReconstructionDepth Map SynthesisEpipolar GeometryLight Field EstimationLight Field ImagingView Synthesis
Light Field (LF) image captured by plenoptic camera can record richer scenario information from our world. But a huge number of Sub-Aperture Images (SAIs) from LF image results in great challenges for coding LFI. Therefore, we choose a subset of SAIs as multi-view video, and encode them with their corresponding depth maps using Multi-view Video plus Depth (MVD) structure. Due to lack of depth maps for SAIs, we propose a cost function to determine the depth map for each SAI preliminarily based on horizontal and vertical Epipolar Plane Images (EPI), respectively. Then an SAI-guided depth enhancement algorithm is designed to optimize the estimated depth maps. Since those unselected SAIs have not been encoded but have been synthesized using the specific texture image and depth map, our LF image coding method can naturally achieve bitrates reduction dramatically with a good performance and outperform other algorithms significantly.
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Christoph Fehn · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004 · 1.3K citations
Light Field Image Processing: An Overview
Gaochang Wu, Belén Masiá, Adrián Jarabo et al. · IEEE Journal of Selected Topics in Signal Processing · 2017 · 582 citations · Full text
Depth from Combining Defocus and Correspondence Using Light-Field Cameras
Michael Tao, Sunil Hadap, Jitendra Malik et al. · 2013 · 499 citations
Accurate depth map estimation from a lenslet light field camera
Hae‐Gon Jeon, Jaesik Park, Gyeongmin Choe et al. · 2015 · 449 citations