Real-Time Fisheye Lens Distortion Correction Using Automatically Generated Streaming Accelerators

Fisheye lenses are often used in scientific or virtual reality applications to enlarge the field of view of a conventional camera. Fisheye lens distortion correction is an image processing application which transforms the distorted fisheye images back to the natural-looking perspective space. This application is characterized by non-linear streaming memory access patterns that make main memory bandwidth a key performance limiter. We have developed a fisheye lens distortion correction system on a custom board that includes a Xilinx Virtex-4 FPGA. We express the application in a high level streaming language, and we utilize Proteus, an architectural synthesis tool, to quickly explore the design space and generate the streaming accelerator best suited for our cost and performance constraints. This paper shows that appropriate ESL tools enable rapid prototyping and design of real-life, performance critical and cost sensitive systems with complex memory access patterns and hardware-software interaction mechanisms.