SNIC
SUPR
SNIC SUPR
Shearlet transform based light field compression
Dnr:

SNIC 2017/3-107

Type:

SNAC Small

Principal Investigator:

Waqas Ahmad

Affiliation:

Mittuniversitetet

Start Date:

2017-11-30

End Date:

2018-12-01

Primary Classification:

10201: Computer Sciences

Webpage:

Allocation

Abstract

Light field acquisition technologies capture angular and spatial information of the scene. The spatial and angular information enables various post processing applications, e.g. 3D scene reconstruction, refocusing, synthetic aperture etc. The plenoptic camera multiplexes spatial and angular information onto a single image. On the other hand, multiple camera system captures each perspective view into a separate image. In both cases, the additional angular information increases the size of acquired data. The recent call for proposal by JPEG Pleno for light field compression reflects the requirement for new solutions for light field compression. In this paper, we present a novel prediction tool for light field compression. A set of sparse views are used to predict the intermediate views using a reconstruction method based on the shearlet transform. The rate distortion analysis for proposed compression scheme shows the significant compression efficiency in low bit-rate scenarios, compare to anchor compression scheme. The sensitivity of human vision system toward compression artifacts in low-bit-rate cases favours the proposed compression scheme over the anchor scheme.