Hardware Acceleration of Division-Free Quadrature-Based Square Rooting Approach for Near-Lossless Compression of Hyperspectral Images
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...
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MDPI AG
2025-02-01
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| Online Access: | https://www.mdpi.com/1424-8220/25/4/1092 |
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| author | Amal Altamimi Belgacem Ben Youssef |
| author_facet | Amal Altamimi Belgacem Ben Youssef |
| author_sort | Amal Altamimi |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-164407ec52684ee38d1f4e86633dff50 |
| institution | DOAJ |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-164407ec52684ee38d1f4e86633dff502025-08-20T02:44:50ZengMDPI AGSensors1424-82202025-02-01254109210.3390/s25041092Hardware Acceleration of Division-Free Quadrature-Based Square Rooting Approach for Near-Lossless Compression of Hyperspectral ImagesAmal Altamimi0Belgacem Ben Youssef1Space Technologies Institute, King Abdulaziz City for Science and Technology, P.O. Box 8612, Riyadh 12354, Saudi ArabiaDepartment of Computer Engineering, College of Computer and Information Sciences, King Saud University, P.O. Box 51178, Riyadh 11543, Saudi ArabiaRecent 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.https://www.mdpi.com/1424-8220/25/4/1092hyperspectral imagingdata compressionhardware accelerationFPGAnear-lossless compressionreal-time processing |
| spellingShingle | Amal Altamimi Belgacem Ben Youssef Hardware Acceleration of Division-Free Quadrature-Based Square Rooting Approach for Near-Lossless Compression of Hyperspectral Images Sensors hyperspectral imaging data compression hardware acceleration FPGA near-lossless compression real-time processing |
| title | Hardware Acceleration of Division-Free Quadrature-Based Square Rooting Approach for Near-Lossless Compression of Hyperspectral Images |
| title_full | Hardware Acceleration of Division-Free Quadrature-Based Square Rooting Approach for Near-Lossless Compression of Hyperspectral Images |
| title_fullStr | Hardware Acceleration of Division-Free Quadrature-Based Square Rooting Approach for Near-Lossless Compression of Hyperspectral Images |
| title_full_unstemmed | Hardware Acceleration of Division-Free Quadrature-Based Square Rooting Approach for Near-Lossless Compression of Hyperspectral Images |
| title_short | Hardware Acceleration of Division-Free Quadrature-Based Square Rooting Approach for Near-Lossless Compression of Hyperspectral Images |
| title_sort | hardware acceleration of division free quadrature based square rooting approach for near lossless compression of hyperspectral images |
| topic | hyperspectral imaging data compression hardware acceleration FPGA near-lossless compression real-time processing |
| url | https://www.mdpi.com/1424-8220/25/4/1092 |
| work_keys_str_mv | AT amalaltamimi hardwareaccelerationofdivisionfreequadraturebasedsquarerootingapproachfornearlosslesscompressionofhyperspectralimages AT belgacembenyoussef hardwareaccelerationofdivisionfreequadraturebasedsquarerootingapproachfornearlosslesscompressionofhyperspectralimages |