An On-Board Satellite Multispectral and Hyperspectral Compressor (MHyC): An Efficient Architecture of a Simple Lossless Algorithm

On-board satellite remote sensing necessitates the data processing blocks to comprise high throughput with low computational complexity to match the high-speed data acquisition with the constraints of resource, power, timing, and downlink bandwidth. This paper presents a high-performance architecture of a simple lossless algorithm (SLA) for on-board satellite multispectral and hyperspectral data compression, which can be configured to all the directional modes of SLA in the band-sequential (BSQ) sampling order. The architecture supports a 16-bit input dynamic range and includes a mode synchronized data handling block along with pipelined implementations of the pre-processing and entropy encoding blocks. A novel adaptation is proposed in the entropy encoder block, which uses a correlation-based adaptation (CBA) in Golomb-Rice (GR) encoding to improve the compression performance of SLA while maintaining the low computational complexity. Kintex KCU-105 evaluation board is used for implementation of the architecture for testing with standard test datasets from the Consultative Committee for Space Data System (CCSDS) corpus of data for multispectral and hyperspectral imagery. The proposed architecture shows comparable compression performance to the low complexity mode of the CCSDS 123.0-B-1 standard and is within $\approx 1$ bits per sample (bps) range in comparison to the default mode of the standard. A throughput of $\approx 4$ Gbps is achieved at a clock frequency of 250 MHz with lesser resource utilization and power consumption compared to the CCSDS 123.0-B-1 standard implementations.