Student research opportunities
Multi-modal imaging system
Project Code: CECS_949
This project is available at the following levels:
PhD
Please note that this project is only for higher degree (postgraduate) applicants.
Keywords:
imaging modality, image sensor, multispectral imaging, hyperspectral imaging, polarisation, plenoptic, lightfield, hardware design, imaging processing, computer vision
Supervisors:
Dr Cong Phuoc HuynhDr Antonio Robles-kelly
Outline:
Recently, several emerging imaging modalities have promised a lot of potential in many application areas. For example, multispectral and hyperspectral images can sample more than three colour values in and beyond the visible spectrum. Polarisation imaging allows for the recovery of the object shape and material properties. Plenoptic imaging can capture the scene depth in one shot.
In this project, we will investigate the possibility of building an all-in-one imaging system that unifies these imaging modalities. This system will be capable of sampling wavelengths, polarisation and incoming light directions so as to offer a richer representation of
the scene than can be delivered by any pre-existing system alone. This opens up great opportunities and provides a worthy research challenge related to the hardware design, image processing and computer vision techniques required to build such a system.
Goals of this project
The objectives of the project are two-fold. Firstly, it aims to seek a practical design of the optics/sensor for image acquisition. Secondly, it aims to develop methods and algorithms to process the acquired imagery for various applications. A number of example applications could be
* Super-resolution and shape analysis.
* High-dynamic range imaging.
* Colour reproduction.
* Soft-ware based simulation of camera controls of focal length, aperture, focus and metering.
Requirements/Prerequisites
This PhD project is suitable for candidates with strong background in mathematics, physics, computer science and engineering and a first class Honours degree in these related areas or equivalent. Good foundations in mathematics (linear algebra, calculus and optimisation) and physics (optics) are essential to the success of the
candidature. In addition, candidates should have good software design and programming skills and experience with C++ and Matlab.
Student Gain
The student will gain a hands-on experience working with both advanced imaging equipment as well as imaging processing and computer vision techniques under the supervision of motivated and experienced researchers in the related areas. In case the research results show potential practicality, the student will be involved in patenting and commercialisation activities.
Background Literature
1. Robles-Kelly, A. & Huynh, C. P., 2013, Imaging Spectroscopy for Scene Analysis, Springer-Verlag, London.
2. Light fields and computational photography. URL: http://graphics.stanford.edu/projects/lightfield/
3. Camera 2.0: New computing platforms for computational photography. URL: http://graphics.stanford.edu/projects/camera-2.0
