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Low Power Architectures for Real-Time Hyperspectral Image Processing
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| The goal of this project is to design and implement re-configurable low power hardware tools for real-time processing of hyperspectral images. The main idea is to use only quantized power-of-2 algorithms in which all multiplications are reduced to simple shifting operations. This will guarantee that the hardware will use the minimum power, provided other design constraints are met. In a previous AISR project, we have designed and developed several multiplier-free algorithms. One important and large component which was not part of that project is ''Spectral Unmixing.'' In hyperspectral images, data are often modeled as linear combinations of radiance spectra. Therefore, the spectral data needs to be ''unmixed'' before usage. In this project, we will develop multiplier-free algorithms for spectral unmixing. We will then design hardware modules for all our DSP algorithms. We will design low-power VLSI architectural modules for several different DSP algorithms including: (a) Fixed digital filters, (b) Adaptive filtering algorithms, (c) Image restoration algorithms, (d) Spectral unmixing algorithms, (e) Adaptive Pulse Code Modulation (ADPCM), (f) Transform coders, and (g) Entropy coders. All of these modules will be designed to be multiplier-free and low-power. These features also translate to low cost and smaller chips. We will combine these modules to build an entire low power system for hyperspectral image restoration and compression. Utah State University/Space Dynamics Laboratory (USU/SDL) has developed a low power computer system for command and control, attitude determination, and telemetry for small spacecrafts. The system has been developed for the 15-kilogram class Ionospheric Observation Nanosatellite Formation (ION-F) satellites. The low-power hyperspectral image processor will be integrated with this system to develop a complete spacecraft system. Since all hardware design is typically done in VHDL or Verilog, it will not be difficult to perform this integration. In fact, we will also integrate the electronics for science instruments with our system. This includes instrumentation for image detection, electron density, electric field, magnetic field and neutral particle motion and composition. The ultimate goal is to build a complete ìspacecraft system on a chip.î |
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