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Image processing tasks in remote sensing and computer vision require an enormous amount of computation, especially in practical real-time applications. An array computer for low-and intermediate-level image processing is designed and implemented based on FPGA. To improve the system usability and the portability of application programs, a parallel image processing software environment is proposed based on the image algebra theory presented by G. X. Ritter. To program the parallel architecture, users need only describe their algorithms with image algebra operations provided in the environment. The environment can automatically select the optimal or approximately optimal parallel codes from the parallel implementation codes library according to the algorithm description and a cost model, and execute the application program. The parallel execution of application programs and the hardware details of the parallel architecture are transparent to users.