Wilfredo E. Lugo-Beauchamp

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Real-time image processing requires high computational and I/O throughputs obtained by use of optoelectronic system solutions. A novel architecture that uses focal-plane optoelectronic-area I/O with a fine-grain, low-memory, single-instruction-multiple-data (SIMD) processor array is presented as an efficient computational solution for real-time(More)
Real-time image processing applications have tremendous computational workloads and I/O throughput requirements. Operation in mobile, portable devices poses stringent resource limitations (size, weight, and power). The SIMD Pixel Processor (SIMPil) has been designed at Georgia Tech to address these problems. In SIMPil, an image sensor array (focal plane) is(More)
Hyperspectral imaging analysis demands large input data sets and in turn requires significant CPU time and memory capacity. Grid Computing has the potential of improving the performance of these types of data and computational intensive applications. In this thesis we describe the design and implementation of Grid-HSI, a Service Oriented Architecture-based(More)
Future military scenarios will rely on advanced imaging sensor technology beyond the visible spectrum to gain total battlefield awareness. Real-time processing of these data streams requires tremendous computational workloads and I/O throughputs. This paper presents three applications for hyper-spectral data streams, vector quantization, region autofocus,(More)
This paper describes the experiences and results on implementing a set of hyperspectral imaging analysis algorithms on the Itanium Processor Family. On Itanium architecture all instructions are transformed into bundles of instructions and these bundles are processed in a parallel fashion by the different functional units. Experimental results show that(More)
Hyperspectral imaging provides the capability to identify and classify materials remotely. The applications of such technology is applied everywhere from medical devices and military targets to environmental sciences. With the ongoing advances in spectrometers (spatial resolution and bits per pixel density) the data gathered is constantly increasing. Some(More)
Goals • Determine parallelization opportunities in various SSI applications, including hyperspectral image processing algorithms and image and video compression algorithms. • Assess the feasibility of portable focal plane processing systems for SSI applications. Significance • SSI applications are characterized by very complex computational workloads that(More)
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