An analysis of aliasing and image restoration performance for digital imaging systems

Date of Award

2014

Degree Name

M.S. in Electrical Engineering

Department

Department of Electrical and Computer Engineering

Advisor/Chair

Advisor: Russell C. Hardie

Abstract

It is desirable to obtain a high image quality when designing an imaging system. The design depends on many factors such as the optics, the pitch, and the cost. The effort to enhance one aspect of the image may reduce the chances of enhancing another one, due to some tradeoffs. There is no imaging system capable of producing an ideal image, since that the system itself presents distortion in the image. When designing an imaging system, some tradeoffs favor aliasing, such as the desire for a wide field of view (FOV) and a high signal to noise ratio (SNR). The reason is that aliasing is less disturbing visually if compared against the noise and blur. Some previous research attempted to define the best combination of the optics and pitch that would result in the best image quality that can be achieved practically. However, those studies may have not considered that the post processing can be conducted inside the imaging system. In this work, we reinspect the optics of the imaging system by taking the post image processing into account. Among the optics, we are more concerned about the aspect of the f-number. Varying the f-number controls the aperture and the focal length, which affect the number of passing light photons, the width of FOV, and the speed of the shutter. Optimizing the f-number would impact the amount of noise, blur, and undersampling contained in an image. To simulate the post processing, various restoration methods are used. The restoration methods are the adaptive Wiener filter (AWF), Wiener filter, lanczos, and the bicubic interpolation. We mainly focus on the AWF and its performance, since it is a super resolution (SR) algorithm that is designed to restore images that are sampled below the Nyquist rate. Despite the fact that the AWF is a SR algorithm, it was built to expect multiple low resolution (LR) images as an input, and was never used to restore images from only one LR image. So, we employ the AWF as a single frame SR algorithm for the first time, and compare its performance against the other three methods, in order to achieve the best f-number that would introduce the best image quality available.

Keywords

Image processing Digital techniques, Image reconstruction, Resolution (Optics), Photography Exposure, Electrical Engineering, Imaging system, image restoration, aliasing, f-number, adaptive Wiener filter, image quality

Rights Statement

Copyright © 2014, author

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