Hardware Acceleration of Division-Free Quadrature-Based Square Rooting Approach for Near-Lossless Compression of Hyperspectral Images

TL;DR

This paper introduces an efficient FPGA-based method for compressing hyperspectral images with minimal data loss, optimized for real-time satellite applications.

Contribution

A novel division-free quadrature-based square rooting method is implemented on FPGA for near-lossless hyperspectral image compression.

Findings

The approach achieves 1611.77 MSps throughput on a Cyclone V FPGA.

It consumes only 0.886 Watts, resulting in 1819.15 MSps/Watt efficiency.

The method outperforms recent state-of-the-art hardware implementations.

Abstract

Recent advancements in hyperspectral imaging have significantly increased the acquired data volume, creating a need for more efficient compression methods for handling the growing storage and transmission demands. These challenges are particularly critical for onboard satellite systems, where power and computational resources are limited, and real-time processing is essential. In this article, we present a novel FPGA-based hardware acceleration of a near-lossless compression technique for hyperspectral images by leveraging a division-free quadrature-based square rooting method. In this regard, the two division operations inherent in the original approach were replaced with pre-computed reciprocals, multiplications, and a geometric series expansion. Optimized for real-time applications, the synthesis results show that our approach achieves a high throughput of 1611.77 Mega Samples per second (MSps) and a low power requirement of 0.886 Watts on the economical Cyclone V FPGA. This results in an efficiency of 1819.15 MSps/Watt, which, to the best of our knowledge, surpasses recent state-of-the-art hardware implementations in the context of near-lossless compression of hyperspectral images.

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