Multi-GPU based near real-time preprocessing and releasing system of optical satellite images

The volume of the image data collected by optical satellites is increasing tremendously nowadays. In this paper, we present our recent research on the multi-graphics processing unit (multi-GPU) based near real-time preprocessing and releasing system (RPRS) of optical satellite images. RPRS consists of two sub-systems, namely, the image preprocessing sub-system and the image releasing sub-system. The image preprocessing sub-system ports the four image processors (i.e. relative radiometric correction, median filtering, modulation transfer function compensation and geometric correction) to the GPUs for execution with the compute unified device architecture (CUDA). Both the basic GPU implementation and three optimization measures are presented. To validate our strategy, an entire ZY-3 nadir image strip consisting of 80 images is used for experiment on the multi-GPU system that consists of four NVIDIA Tesla M2050 GPUs. The results show that the efficiency of the processors is substantially accelerated by the use of GPU. The speedup ratios are between 10.94 and 44.89. Moreover, when using all the four GPUs, the processing of the entire image strip only costs 19 min 45 s, which could meet the near realtime preprocessing requirement. The image releasing system affords the direct visualization of the georeferenced images on the geographic base map of GeoGlobe, a Google Earth like 3D spatial information releasing platform developed by State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, China. It is very convenient for the follow-up relevant applications.