Information theoretic performance evaluation of 3D integral imaging
Abstract
Integral imaging (InIm) has proved useful for three-dimensional (3D) object sensing, visualization, and classification of partially occluded objects. This paper presents an information-theoretic approach for simulating and evaluating the integral imaging capture and reconstruction process. We utilize mutual information (MI) as a metric for evaluating the fidelity of the reconstructed 3D scene. Also we consider passive depth estimation using mutual information. We apply this formulation for optimal pitch estimation of integral-imaging capture and reconstruction to maximize the longitudinal resolution. The effect of partial occlusion in integral imaging 3D reconstruction using mutual information is evaluated. Computer simulation tests and experiments are presented.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Nov 08, 2022
- Source ID
- 10.1364/oe.475086
Entities
People
- Bahram Javidi
- Gokul Krishnan
- Pranav Wani
- Timothy O'Connor
Organizations
- Air Force Office of Scientific Research
- Office of Naval Research
- University of Connecticut