Video compression aims to reduce video file size without impacting visual quality. Existing algorithms mostly use transform coders to convert information from the spatial to frequency domain, and attenuate or remove high frequency components from the sequence. This enables the omission of a large proportion of high frequency information with no discernible visual impact. Sprite-based compression encodes large portions of a scene as a single object in the video sequence, recreating the object in subsequent frames by warping or morphing the sprite to mimic changes in subsequent frames. This thesis sought to improve several aspects of existing sprite based compression approaches, employing a temporal motion model using a low order polynomial to represent the motion of an object across multiple frames in a single model rather than a series of models. The main outcome is the demonstration that motion models used by sprite based video compression can be extended to a full three dimensional model, reducing the overall size of the model, and improving the quality of the sequence at low bit rates. A second outcome is the demonstration that super-resolution processing is not necessary if lanczos spatial interpolation is used instead of bilinear or bi-cubic interpolation, resulting in a savings in computational time and resources. A third outcome is the introduction of a new blending model used to generate image mosaics that improves the quality of the synthesised sequence when zoom is present in the sequence for a given bit-rate. A final outcome is demonstrating that performing superresolution processing and sub-sampling back to the original resolution prior to compression provides benefits in some circumstances.