Light Field Reconstruction Using Shearlet Transform
Research output: Contribution to journal › Article › Scientific › peer-review
|Number of pages||15|
|Journal||IEEE Transactions on Pattern Analysis and Machine Intelligence|
|Early online date||16 Jan 2017|
|Publication status||Published - 2018|
|Publication type||A1 Journal article-refereed|
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.