Image processing techniques for underwater single photon imaging


The aim of the project is to improve and automate the data processing pipeline of underwater imaging systems currently under development at HWU.


  1. Improving the quality of images for underwater single-photon active/passive data
  2. Sensor fusion with single-photon Lidar and sonar data
  3. Adaptive sensing


The development of single-photon detector arrays has opened exciting opportunities for passive and active imaging in extreme conditions (high-speed, low-illumination regimes), and in particular for imaging in scattering underwater environments. In this project we will first investigate multiband (multispectral/polarimetric) imaging in the high-background, low-photon regime, where traditional image restoration methods fail due to the non-Gaussian noise statistics. In the context of 3D imaging, single-photon Lidar offers unprecedented sensitivity and range resolution compared to alternative technologies but needs to be guided (e.g., by restricting the depth of field) to reduce the impact of noise. Here, we propose to use sonar data to coarsely identify underwater objects of interest and adaptively optimized the single-photon Lidar system. From a computational viewpoint, this project will investigate physics-based models as well as data-driven models for fusion and computational complexity analysis will be crucial to ensure rapid sensor feedback/control.

Research theme: 

Principal supervisor: 

Dr Aurora Maccarone
Heriot-Watt University, School of Engineering

Assistant supervisor: 

Dr Yoann Altmann
Heriot-Watt University, School of Engineering and Physical Sciences

Dr Istvan Gyongy
University of Edinburgh, School of Engineering