Designing Coded Aperture Camera Based on PCA and NMF for Light Field Acquisition

Yusuke YAGI  Keita TAKAHASHI  Toshiaki FUJII  Toshiki SONODA  Hajime NAGAHARA  

IEICE TRANSACTIONS on Information and Systems   Vol.E101-D   No.9   pp.2190-2200
Publication Date: 2018/09/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2017PCP0007
Type of Manuscript: Special Section PAPER (Special Section on Picture Coding and Image Media Processing)
light field,  coded aperture,  principal component analysis,  non-negative matrix factorization,  

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A light field, which is often understood as a set of dense multi-view images, has been utilized in various 2D/3D applications. Efficient light field acquisition using a coded aperture camera is the target problem considered in this paper. Specifically, the entire light field, which consists of many images, should be reconstructed from only a few images that are captured through different aperture patterns. In previous work, this problem has often been discussed from the context of compressed sensing (CS), where sparse representations on a pre-trained dictionary or basis are explored to reconstruct the light field. In contrast, we formulated this problem from the perspective of principal component analysis (PCA) and non-negative matrix factorization (NMF), where only a small number of basis vectors are selected in advance based on the analysis of the training dataset. From this formulation, we derived optimal non-negative aperture patterns and a straight-forward reconstruction algorithm. Even though our method is based on conventional techniques, it has proven to be more accurate and much faster than a state-of-the-art CS-based method.