Edge Computing-Based SAT-Video Coding for Remote Sensing

Abstract

This paper proposes an edge computing-based video coding implementation on an Earth observation satellite (SAT-video coding), which can encode video using limited resources and the power of mini/microsatellites. SAT-video coding proposes a hardware-related quantization (Q) function, hardware reduction of the motion estimation (ME) method, and simplified entropy coding (EC), which reduces the computation complexity. The hardware-related Q reduces hardware resource and power consumption by 72% and 55%, respectively, compared with traditional Q implementation. The hardware reduction of ME reduces resource use compared with regular ME implementation (59% of lookup tables [LUTs] and 79% of Registers). The total number of LUTs used for the simplified EC function is also much lower than other EC hardware implementations. The SAT-video encoder IP uses fewer hardware resources, and the power consumption is estimated at 0.0894 W at a high working frequency (125 MHz). The SAT-video encoding speed is 18.95 frames per second for $2560\times 2560$ video. Therefore, the proposed SAT-video coding is an edge computation suitable for micro/minisatellites. The coding efficiency records the highest compression ratio at 33.8, with a peak signal-to-noise ratio of 34.46 dB. With the important task of designing edge computing based on satellite video encoding, these are adequate values for remote sensing video.

Keywords

• Video compression
• remote sensing video
• hardware acceleration
• satellite