Optimal periodic memory allocation for image processing with multiple windows

One major issue in designing image processors is to design a memory system that supports parallel access with a simple interconnection network. This paper presents an efficient memory allocation to minimize the number of memory modules and processing elements with a parallel access capability when multiple windows with arbitrary shapes are specified. This paper also presents an efficient search method based on regularity of window-type image processing. We give some practical examples including a stereo-matching processor for acquiring 3-D information, and an optical-flow processor for motion estimation. These examples show that the numbers of memory modules are reduced to 2.7% and 10%, respectively, in comparison with a basic approach. It is also shown that the search time is less than 1 ms for practical image sizes and window sizes.