The image blurring that results from moving a camera whilst the shutter is open is normally
regarded as undesirable. However, the blurring of the images contains hidden information
which can be extracted to give information about the captured scene. Information encapsulated
within this blur allows the light rays present within the scene to be recovered. Given the correct
recovery of the light rays that form a blurred image, a sharp image of the scene can be generated
for an arbitrary camera location. Therefore, rather than resharpening an image with motion
blur, the goal of the work contained within this thesis is to recover the light rays within the
scene
Recovery of the light rays within the scene is achieved by using a layer based model to represent
objects within the scene as planes at discrete depths, and by using an extension to the level set
method, to segment the blurred image into planes at different depths. Knowledge of the layer
boundaries is then used to recover the surfaces of the layers, and hence a model of the scene in
three dimensions. The algorithm described in this thesis has been successfully tested on real
and synthetic images constructed from fronto-parallel planes, with the scene being recovered
accurately from all positions within the original path of the camera.