We have developed the University of Washington Image Computing Library (UWICL), the high-performance image processing library for a next-generation mediaprocessor currently under development, named the Media Accelerated Processor (MAP1000). The primary goal of this library is to provide the algorithm developers and application programmers with a flexible and efficient library of core image computing functions. The UWICL is organized as a set of three hierarchical layers. Each function in this multilayered framework consists of an application module, a function module, and a tight-loop module. The MAP has an intelligent DMA controller called the Data Streamer that allows efficient data flow management. In cache-based architectures, streaming image data from the external memory generates many costly data-cache misses, in many cases leading to a severe performance bottleneck. The MAP's Data Streamer is designed to address this problem. To reduce the number of the data-cache misses further, a ping-ponging data flow scheme is employed in UWICL functions, i.e., while execution units are processing a block of data currently in the data cache, the Data Streamer brings the next data block to the data cache before it is actually needed. We compare the performance of key imaging functions on the MAP and the Texas Instruments TMS320C80, one of the most powerful mediaprocessors currently available. Typically, a MAP function is 1.5 to 6.6 times faster than the corresponding TMS320C80 implementation. Also, we demonstrate the advantages of the UWICL's multilayered library organization over the single-layered approach with an example in implementing the Canny's edge detector. The multilayered implementation of this algorithm outperforms the single- layered version by 26%.