Publication: Implementación sobre FPGA de un algoritmo de compresión de imágenes hiperespectrales bajo el estándar CCSDS 123.0-B-1
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2016
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Abstract
A lo largo de la historia, nuestro planeta ha atravesado numerosas y diferentes etapas. Sin embargo, desde finales del cretácico no se vivía un cambio tan rápido como el actual. Y a la cabeza del cambio, nosotros, el ser humano. De igual manera que somos la causa, debemos ser también la solución, y el análisis a gran escala de la tierra está siendo un punto de interés para la comunidad científica en los últimos años. Prueba de ello es que, cada vez con más frecuencia, se lanzan gran cantidad de satélites cuya finalidad es el análisis, mediante fotografías, de la superficie terrestre. Una de las técnicas más versátiles para este análisis es la toma de imágenes hiperespectrales, donde no solo se captura el espectro visible, sino numerosas longitudes de onda. Suponen, eso sí un reto tecnológico, pues los sensores consumen más energía y las imágenes más memoria, ambos recursos escasos en el espacio. Dado que el análisis se hace en tierra firme, es importante una transmisión de datos eficaz y rápida. Por ello creemos que la compresión en tiempo real mediante FPGAs es la solución idónea, combinando un bajo consumo con una alta tasa de compresión, posibilitando el análisis ininterrumpido del astro en el que vivimos. En este trabajo de fin de grado se ha realizado una implementación sobre FPGA, utilizando VHDL, del estándar CCSDS 123. Este está diseñado para la compresión sin pérdida de imágenes hiperespectrales, y permite una amplia gama de configuraciones para adaptarse de manera óptima a cualquier tipo de imagen. Se ha comprobado exitosamente la validez de la implementación comparando los resultados obtenidos con otras implementaciones (software) existentes. Las principales ventajas que presentamos aquí es que se posibilita la compresión en tiempo real, obteniendo además un rendimiento energético muy prometedor. Estos resultados mejoran notablemente los de una implementación software del algoritmo, y permitirán la compresión de las imágenes a bordo de los satélites que las toman.
Throughout history, our planet has endured many different climates. However, a change as fast as the current one had not been seen since the end of the cretacic era. We, as humans, are leading this change. Being the cause, it is our duty to also be the remedy. The analysis of the earth as a whole has been a hot topic for the scientific community in the past few years. Proof of which is that, with increasing frequency, satellites are being launched whose objective is to analyze, using photography, our planet’s surface. One of the most versatile techniques for this purpose is hyperspectral imaging, where not only the visible spectrum is captured, but also lots of different wavelenghts. This presents, however, a technical challenge, given the increased power consumption of the sensors, and the increased storage needs for the captured data. Both are scarse resources up in space. Since data processing is done back on Earth, it is of our interest a quick and effective link with the satellites. This is why we believe that real time compression using FPGAs is the ideal solution, combining both low power chips and a high compression rate, opening the possibility of an uninterrupted analysis of the planet we live in. In this work, an implementation of the CCSDS 123 standard has been made using VHDL, aiming for its use on FPGAs. The standard’s goal is to losslessly compress hyperspectral images, allowing optimal compression for any kind of image with its many parameters. Validity of the algorithm has been tested against previous implementations, with our hardware one giving the same results as its software counterparts. The main advantage we get is the ability to compress in real time, paired with a very promising power efficiency. These results notably improve those of the software implementation, and will allow on-board compression of images in the same satellites they are taken from.
Throughout history, our planet has endured many different climates. However, a change as fast as the current one had not been seen since the end of the cretacic era. We, as humans, are leading this change. Being the cause, it is our duty to also be the remedy. The analysis of the earth as a whole has been a hot topic for the scientific community in the past few years. Proof of which is that, with increasing frequency, satellites are being launched whose objective is to analyze, using photography, our planet’s surface. One of the most versatile techniques for this purpose is hyperspectral imaging, where not only the visible spectrum is captured, but also lots of different wavelenghts. This presents, however, a technical challenge, given the increased power consumption of the sensors, and the increased storage needs for the captured data. Both are scarse resources up in space. Since data processing is done back on Earth, it is of our interest a quick and effective link with the satellites. This is why we believe that real time compression using FPGAs is the ideal solution, combining both low power chips and a high compression rate, opening the possibility of an uninterrupted analysis of the planet we live in. In this work, an implementation of the CCSDS 123 standard has been made using VHDL, aiming for its use on FPGAs. The standard’s goal is to losslessly compress hyperspectral images, allowing optimal compression for any kind of image with its many parameters. Validity of the algorithm has been tested against previous implementations, with our hardware one giving the same results as its software counterparts. The main advantage we get is the ability to compress in real time, paired with a very promising power efficiency. These results notably improve those of the software implementation, and will allow on-board compression of images in the same satellites they are taken from.
Description
Trabajo de Fin de Grado en Ingeniería Informática y Matemáticas (Universidad Complutense, Facultad de Informática, curso 2015/2016)