Real-time image compression using SIMD architectures

Today, in the digitized satellite image domain, the need for high-dimension images is increasing considerably. To transmit or to store such images (more than 6000/spl times/6000 pixels), we need to reduce their data volume, and so we have to use image compression techniques. In most cases, these operations have to be processed in real time. The large amount of computations required by classical image compression algorithms prohibits the use of common sequential processors. To solve this problem, CEA (in collaboration with CNES) has tried to define the best-suited architecture for image compression. In order to achieve this aim, we developed and evaluated a new parallel image compression algorithm for general-purpose parallel computers using data-parallelism. This paper presents this new parallel image compression algorithm. We present implementation results on several parallel computers. We also examine load balancing and data mapping problems. We end by defining optimal characteristics of the parallel machine for real-time image compression.