UC San Diego
Physical Optics Based Computational Imaging Systems
- Author(s): Olivas, Stephen Joseph
- et al.
There is an ongoing demand on behalf of the consumer, medical and military industries to make lighter weight, higher resolution, wider field-of-view and extended depth- of-focus cameras. This leads to design trade-offs between performance and cost, be it size, weight, power, or expense. This has brought attention to finding new ways to extend the design space while adhering to cost constraints. Extending the functionality of an imager in order to achieve extraordinary performance is a common theme of computational imaging, a field of study which uses additional hardware along with tailored algorithms to formulate and solve inverse problems in imaging. This dissertation details four specific systems within this emerging field: a Fiber Bundle Relayed Imaging System, an Extended Depth-of-Focus Imaging System, a Platform Motion Blur Image Restoration System, and a Compressive Imaging System. The Fiber Bundle Relayed Imaging System is part of a larger project, where the work presented in this thesis was to use image processing techniques to mitigate problems inherent to fiber bundle image relay and then, form high-resolution wide field-of-view panoramas captured from multiple sensors within a custom state-of-the-art imager. The Extended Depth-of-Focus System goals were to characterize the angular and depth dependence of the PSF of a focal swept imager in order to increase the acceptably focused imaged scene depth. The goal of the Platform Motion Blur Image Restoration System was to build a system that can capture a high signal-to-noise ratio (SNR), long-exposure image which is inherently blurred while at the same time capturing motion data using additional optical sensors in order to deblur the degraded images. Lastly, the objective of the Compressive Imager was to design and build a system functionally similar to the Single Pixel Camera and use it to test new sampling methods for image generation and to characterize it against a traditional camera. These computational imaging systems share a common theme in that they seek to accomplish camera designs that meet more demanding system requirements through the use of additional measurements made possible by hardware modifications, while relying on modeling and computational methods in order to provide valuable scene information