Cloud Segmentation Accelerator Design for Low Data Transmission Rate on Satellite Payload

This paper proposes an optimized cloud segmentation accelerator to enable low data rate transmission in satellite payload applications. The system employs an advanced cloud detection and segmentation framework to distinguish cloud-covered and cloud-free regions in high resolution satellite imagery accurately. A quantized U-Net architecture has been developed with a focus on efficient resource utilization, tailored specifically for FPGA implementation. This design is built upon the H.265 video encoder, significantly reducing bandwidth usage while ensuring high-quality image output. Experimental results highlight impressive segmentation accuracy, achieving a mean Intersection over Union (mIoU) of 85.64%. The architecture is also notable for its low resource consumption, with only 0.27M parameters and 5.2 GFLOPs, along with minimal power requirements of just 0.16W. These attributes make this solution an ideal choice for edge deployment on satellite platforms.