This thesis explores methods for enhancing digital image-like sensations which might be similar to those experienced by blind users of electronic visual prostheses. Visual prostheses, otherwise referred to as artificial vision systems or bionic eyes, may operate at ultra low image quality and information levels as opposed to more common electronic displays such as televisions, for which our expectations of image quality are much higher. The scope of the research is limited to enhancement by digital image processing: that is, by manipulating the content of images presented to the user. The work was undertaken to improve the effectiveness of visual prostheses in representing the visible world. Presently visual prosthesis development is limited to animal models in Australia and prototype human trials overseas. Consequently this thesis deals with simulated vision experiments using normally sighted viewers. The experiments involve an original application of existing image processing techniques to the field of low quality vision anticipated from visual prostheses. Resulting from this work are firstly recommendations for effective image processing methods for enhancing viewer perception when using visual prosthesis prototypes. Although limited to low quality images, recognition of some objects can still be achieved, and it is useful for a viewer to be presented with several variations of the image representing different processing methods. Scene understanding can be improved by incorporating Region-of-Interest techniques that identify salient areas within images and allow a user to zoom into that area of the image. Also there is some benefit in tailoring the image processing depending on the type of scene. Secondly the research involved the construction of a metric for basic information required for the interpretation of a visual scene at low image quality. The amount of information content within an image was quantified using inherent attributes of the image and shown to be positively correlated with the ability of the image to be recognised at low quality.