Tiling and demand driven evaluation for picture processing

We propose a software architecture for picture processing that allows efficient memory management when algorithms with many operators are applied to large images, and that allows automated parallelization. This architecture relies on image tiling and operators with a call back function that evaluate image tiles on demand. Several tiling strategies with and without overlapping are discussed. The complexity of this evaluation strategy is hidden to application programs. This is shown with a sample program. This architecture is well suited for neighborhood operators such as convolutions and mathematical morphology operators.