Sub-pixel techniques to improve spatial resolution

Image acquisition using a scene sampling device generally results in a loss of fidelity in the acquired image, particularly if the scene contains high frequency features. Acquired images are also degraded by the blurring effects of acquisition filtering, image reconstruction, and additive noise effects. to compensate for these degradations, a digital restoration filter that attempts to partially eliminate the blurring while avoiding amplification of the noise effects is needed. In addition, to compensate for undersampling, a subpixel technique known as microscanning is required. This dissertation provides research into the spatial resolution enhancement of digital images based on subpixel techniques that will help to minimize the impact of these degradations. Subpixel techniques investigated include microscanning and estimation of the function that measures the amount of blurring incurred during acquisition. These techniques will be used in conjunction with a constrained least squares restoration filter to achieve the best possible representation of the original scene.