FAST PIECEWISE LINEAR PREDICTORS FOR LOSSLESS COMPRESSION OF HYPERSPECTRAL IMAGERY

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" FAST PIECEWISE LINEAR PREDICTORS FOR LOSSLESS COMPRESSION OF HYPERSPECTRAL IMAGERY "

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	151918
Doc. No	:	ET23710
Main Entry	:	Leila Susana Rodrکguez del Roک
Title Proper	:	FAST PIECEWISE LINEAR PREDICTORS FOR LOSSLESS COMPRESSION OF HYPERSPECTRAL IMAGERY
Note	:	This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract	:	Image compression of hyperspectral is necessary because of the large storagerequirements. The main objective of this research is to develop and implement fast andgood predictors, for use in lossless compression of hyperspectral images. Thealgorithms developed in this research are compared in terms of compressionperformance and computational complexity against the best existent algorithms. Thesebenchmark algorithms are LOCO-I and CALIC-Extended. Lossless compressionalgorithms are typically divided into two stages, a prediction stage to eliminateredundancy and a coding stage. The predictors can utilize pixels of the same spectral.............-....,....-...,..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject	:	Electericl tess
	:	برق
electronic file name	:	TL46965.pdf
Title and statement of responsibility and	:	FAST PIECEWISE LINEAR PREDICTORS FOR LOSSLESS COMPRESSION OF HYPERSPECTRAL IMAGERY [Thesis]