Title Details: | |
Laboratory Exercise: Hyperspectral Imaging |
|
Authors: |
Dasygenis, Minas Soudris, Dimitrios |
Description: | |
Abstract: |
In recent years, Hyperspectral Imaging (HSI) has paved its way into a range of applications, from environmental monitoring to high-speed detection and real-time food processing. The enhancement of this technology's detection capabilities is based on the increased processing abilities of the computing units supporting hyperspectral imaging sensors. In this direction, hardware accelerators based on Field Programmable Gate Arrays (FPGAs) have attracted the interest of the scientific community due to their rapid processing capabilities, low power consumption, and the reconfigurability that these platforms offer. To date, the effective programming of these devices is usually done with hardware description languages such as VHDL or Verilog. In the current work, a parametric VHDL core of a hyperspectral imaging system with multiple configurations will be developed on the Zynq SoC FPGA by Xilinx. This work is part of a research project that has already been published.
|
Linguistic Editors: |
Kagiadaki, Sofia |
Technical Editors: |
Dasygenis, Minas |
Graphic Editors: |
Dasygenis, Minas |
Type: |
Chapter |
Creation Date: | 28-08-2024 |
Item Details: | |
License: |
Attribution - NonCommercial - ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
Handle | http://hdl.handle.net/11419/13879 |
Bibliographic Reference: | Dasygenis, M., & Soudris, D. (2024). Laboratory Exercise: Hyperspectral Imaging [Chapter]. In Dasygenis, M., & Soudris, D. 2024. Internet of Things Computing [Undergraduate textbook]. Kallipos, Open Academic Editions. https://hdl.handle.net/11419/13879 |
Language: |
Greek |
Is Part of: |
Internet of Things Computing |
Publication Origin: |
Kallipos, Open Academic Editions |