Hardware Implementation of the CCSDS 123.0-B-2 Near-Lossless Compression Standard Following an HLS Design Methodology

Yubal Barrios,Raúl Guerra,Roberto Sarmiento,Antonio Sánchez

doi:10.3390/rs13214388

Abstract

The increment in the use of high-resolution imaging sensors on-board satellites motivates the use of on-board image compression, mainly due to restrictions in terms of both hardware (computational and storage resources) and downlink bandwidth with the ground. This work presents a compression solution based on the CCSDS 123.0-B-2 near-lossless compression standard for multi- and hyperspectral images, which deals with the high amount of data acquired by these next-generation sensors. The proposed approach has been developed following an HLS design methodology, accelerating design time and obtaining good system performance. The compressor is comprised by two main stages, a predictor and a hybrid encoder, designed in Band-Interleaved by Line (BIL) order and optimized to achieve a trade-off between throughput and logic resources utilization. This solution has been mapped on a Xilinx Kintex UltraScale XCKU040 FPGA and targeting AVIRIS images, reaching a throughput of 12.5 MSamples/s and consuming only the 7% of LUTs and around the 14% of dedicated memory blocks available in the device. To the best of our knowledge, this is the first fully-compliant hardware implementation of the CCSDS 123.0-B-2 near-lossless compression standard available in the state of the art.

Highlights

The proposed solution has been initially verified by simulation during the different development stages, in order to ensure its correct behavior once it is mapped on hardware
The proposed compression solution has been mapped on a Xilinx KCU105 development board, which includes a Kintex UltraScale FPGA (XCKU040-2FFVA1156E)
A hardware implementation of the 123.0-B-2 compression standard from the Consultative Committee for Space Data Systems (CCSDS) has been presented, which was accomplished following an High-Level Synthesis (HLS) design methodology. This standard is conceived for the lossless to near-lossless compression of multi- and hyperspectral images, featuring a reduced computational complexity which is well suited for space missions

Summary

Introduction

Hyperspectral imaging sensors are gaining interest in the space industry since they provide useful information at different wavelengths for some Remote Sensing applications, such as surface characterization and monitoring, or target detection and tracking. It is expected that these constraints become more stringent during the years, since nextgeneration hyperspectral imaging sensors will increase both the pixel resolution and the scene size [2,3], even incorporating the acquisition of multispectral video. For all these reasons, both academia and companies linked to the space industry are developing efficient solutions for on-board image compression, taking advantage of the high correlation between adjacent wavelengths in 3D images

Methods

Results

Conclusion