Abstract
We consider the problem of reconstructing densely sampled light field (DSLF) from sparse camera views. In our previous work, the DSLF has been reconstructed by processing epipolar-plane images (EPI) employing sparse regularization in shearlet transform domain. With the aim to avoid redundant processing and reduce the overall reconstruction time, in this paper, we propose algorithm modifications in three directions. First, we modify the basic algorithm by offering a faster and more stable iterative procedure. Second, we elaborate on the proper use of color redundancy by studying the effect of reconstruction of an average intensity channel and its use as a guiding mode for colorizing the three color channels. Third, we explore similarities between EPIs by their grouping and joint processing or by effective decorrelation to get an initial estimate for the basic iterative procedure. We are specifically interested in GPU-based computations allowing an efficient implementation of the shearlet transform. We quantify our three main approaches to accelerated processing over a wide collection of horizontal as well as full-parallax datasets.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Journal of Selected Topics in Signal Processing
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
