Literature DB >> 28092525

Light Field Reconstruction Using Shearlet Transform.

Suren Vagharshakyan, Robert Bregovic, Atanas Gotchev.   

Abstract

In this article we develop an image based rendering technique based on light field reconstruction from a limited set of perspective views acquired by cameras. Our approach utilizes sparse representation of epipolar-plane images (EPI) in shearlet transform domain. The shearlet transform has been specifically modified to handle the straight lines characteristic for EPI. The devised iterative regularization algorithm based on adaptive thresholding provides high-quality reconstruction results for relatively big disparities between neighboring views. The generated densely sampled light field of a given 3D scene is thus suitable for all applications which require light field reconstruction. The proposed algorithm compares favorably against state of the art depth image based rendering techniques and shows superior performance specifically in reconstructing scenes containing semi-transparent objects.

Year:  2017        PMID: 28092525     DOI: 10.1109/TPAMI.2017.2653101

Source DB:  PubMed          Journal:  IEEE Trans Pattern Anal Mach Intell        ISSN: 0098-5589            Impact factor:   6.226


  3 in total

1.  End-to-End Residual Network for Light Field Reconstruction on Raw Images and View Image Stacks.

Authors:  Ahmed Salem; Hatem Ibrahem; Bilel Yagoub; Hyun-Soo Kang
Journal:  Sensors (Basel)       Date:  2022-05-06       Impact factor: 3.847

2.  RCA-LF: Dense Light Field Reconstruction Using Residual Channel Attention Networks.

Authors:  Ahmed Salem; Hatem Ibrahem; Hyun-Soo Kang
Journal:  Sensors (Basel)       Date:  2022-07-14       Impact factor: 3.847

3.  Light Field Reconstruction Using Residual Networks on Raw Images.

Authors:  Ahmed Salem; Hatem Ibrahem; Hyun-Soo Kang
Journal:  Sensors (Basel)       Date:  2022-03-02       Impact factor: 3.576

  3 in total

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