Fractal Video Compression in OpenCL: An Evaluation of CPUs, GPUs, and FPGAs as Acceleration Platforms

Fractal compression is an efficient technique for image and video encoding that uses the concept of self-referential codes. Although offering compression quality that matches or exceeds traditional techniques with a simpler and faster decoding process, fractal techniques have not gained widespread acceptance due to the computationally intensive nature of its encoding algorithm. In this paper, we present a real-time implementation of a fractal compression algorithm in OpenCL [1]. We show how the algorithm can be efficiently implemented in OpenCL and optimized for multi-CPUs, GPUs, and FPGAs. We demonstrate that the core computation implemented on the FPGA through OpenCL is 3x faster than a high-end GPU and 114x faster than a multi-core CPU, with significant power advantages. We also compare to a hand coded FPGA implementation to showcase the effectiveness of an OpenCL-to-FPGA compilation tool.