A tutorial overview of how selected computer-vision-related algorithms can be mapped onto reconfigurable parallel-processing systems is presented. The reconfigurable parallel-processing system assumed for the discussions here is a multiprocessor system capable of mixed-mode parallelism; that is, it can operate in either the SIMD (single instruction, multiple data) or MIMD (multiple instruction, multiple data) modes of parallelism and can dynamically switch between modes at instruction-level granularity with generally negligible overhead. In addition, it can be partitioned into independent or communicating submachines, each having the same characteristics as the original machine. Furthermore, this reconfigurable system model uses as a flexible multistage cube interconnection network, which allows the connection patterns among the processors to be varied. It is demonstrated how reconfigurability can be used by reviewing and examining five computer-vision-related algorithms, each one emphasizing a different aspect of reconfigurability.