Over the past 3 billion years, photosynthetic organisms including higher plants, cyanobacteria and microalgae have evolved intricate light capturing interfaces capable of harnessing the huge energy resource of the sun (>2000x global energy demand) to produce the biomass, food and fuels which supports life on earth. As the global population expands, and with it food and fuel demand, it is becoming increasingly important to understand the structure and function of the complex and dynamic machinery of photosynthetic organisms. This is because these intricate photosynthetic systems provide invaluable blueprints for the design of next-generation solar-driven microalgaebased and bio-inspired artificial systems.Microalgae-based systems can be located on non-arable land to produce food, fuel and high value products, in many cases using salt water. Microalgae systems have already achieved demonstration scale and the ability to produce crude oil at a price of ~$230 barrel. Through further optimization, renewable oil prices of $100 barrel could be achievable, opening the path to commercial deployment.The first step of all biofuel production is light capture and optimizing its efficiency. However, this requires a detailed structural knowledge of photosynthetic interfaces spanning the cellular to atomic resolution range. The advances of diverse, multi-scale imaging techniques, including highresolution single particle analysis (SPA), crystallography and electron tomography now provides a path to reveal the structure and dynamics of the photosynthetic machinery. Electron tomographic data provide unprecedented opportunities to resolve cells to molecular resolution while modern SPA, electron and X-ray crystallography and NMR can resolve the atomic resolution structure of proteins. This project is focused on bridging the gap between these techniques by developing advanced edge detection algorithms for automated tomogram segmentation to the molecular level, to facilitate molecular docking of atomic resolution protein structures and so, the development of atomic resolution atlases of the photosynthetic machinery.Chapter 1 reviews the technology drivers for the development of solar fuel systems, the process of photosynthesis, advances in imaging and image processing technologies. The noise contamination of these images and more specifically the different types of noise reduction algorithms used to reduce its effects are reviewed. Edge detection and segmentation algorithms including manual and semi-automated segmentation, thresholding, gradient-based edge detectors, canny edge detetcor, the snake algorithm, the watershed transform, bilateral edge filter, Laplacian of Gaussian (LoG) and arbitrary Z-crossings are next reviewed to evaluate the state of the art in terms of tomogram segmentation and challenges that must be overvome to achieve molecular segmentation.Chapter 2 describes the design and development of the automated bilateral edge (3D BLE) filter for detection of macromolecular complexes. 3D BLE was found to detect obj...