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This thesis addresses the problem of calibrating a stereoscopic camera with a minimum of necessary post-processing. This is achieved through a two step procedure, the first step of which is a calibration of the sensors in rotation by means of laser diffraction, without attached lenses. The second step involves attaching the lenses and using a simplified conventional image-based calibration to determine the effects of motions of the optical centres due to lens focusing. Mounting considerations and long-term stability are also addressed. This method enables the construction of a stereoscopic camera which requires no interpolative rectification, with the calibration maintaining accuracy over a range of focal distances. Such a camera is built and calibrated, and tested to demonstrate the validity of the predicted error estimates. This approach is shown to be effective in producing stereoscopic images for display which meet the requirements of the human visual system. A comparison of this approach with previously published methods is presented. Some or all of the techniques described in this thesis may be incorporated into existing calibration schemes to improve the quality of the produced stereoscopic images. The improvements provided by a hardware calibration as described may be especially valuable in applications where maintaining full sensor resolution in the displayed image is desired.

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The transmission of digital colour images is rapidly becoming popular on mobile telephones, Personal Digital Assistant (PDA) technology and other wireless based image services. However, transmitting digital colour images via mobile devices is badly affected by low air bandwidth. Advances in communications Channels (example 3G communication network) go some way to addressing this problem but the rapid increase in traffic and demand for ever better quality images, means that effective data compression techniques are essential for transmitting and storing digital images. The main objective of this thesis is to offer a novel image compression technique that can help to overcome the bandwidth problem. This thesis has investigated and implemented three different wavelet-based compression schemes with a focus on a suitable compression method for mobile applications. The first described algorithm is a dual wavelet compression algorithm, which is a modified conventional wavelet compression method. The algorithm uses different wavelet filters to decompose the luminance and chrominance components separately. In addition, different levels of decomposition can also be applied to each component separately. The second algorithm is segmented wavelet-based, which segments an image into its smooth and nonsmooth parts. Different wavelet filters are then applied to the segmented parts of the image. Finally, the third algorithm is the hybrid wavelet-based compression System (HWCS), where the subject of interest is cropped and is then compressed using a wavelet-based method. The details of the background are reduced by averaging it and sending the background separately from the compressed subject of interest. The final image is reconstructed by replacing the averaged background image pixels with the compressed cropped image. For each algorithm the experimental results presented in this thesis clearly demonstrated that encoder output can be effectively reduced while maintaining an acceptable image visual quality particularly when compared to a conventional wavelet-based compression scheme.