Computational Imaging for conformal imaging systems

Conventional imaging systems are relatively bulky and typically employ a single large lens within an approximately cuboid imaging systems. This makes them difficult to integrate into many platforms, particularly those employing extreme aerodynamic surfaces such as nose cones. This project will aim to develop computational imaging systems that demonstrate high-resolution imaging from conformal surfaces using multi-aperture techniques developed as mathematical models at Glasgow, including: (1) Asymmetric Fourier-domain multicamera imaging. Variations of this theme are illustrated in the models below showing how multiple rectangular apertures can be combined to yield isotropic, high-resolution imaging. (2) Computational imaging for mitigation of aberrations introduced by imaging through aerodynamic surfaces. A key aim in this work is develop imaging systems optimised for detection of key objects rather than for detection of images. In this case, techniques such as machine learning can operate directly on aberrated, superimposed images for detection of targets.