A fast hybrid block-sorting algorithm for lossless interferometric data compression

Gianfranco Basti; Antonio Luigi Perrone

doi:10.1117/12.487504

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4 August 2003 A fast hybrid block-sorting algorithm for lossless interferometric data compression

Gianfranco Basti, Antonio Luigi Perrone

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Proceedings Volume 5103, Intelligent Computing: Theory and Applications; (2003) https://doi.org/10.1117/12.487504
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

In this paper, we present an evolution of the classical Barrow-Wheeler Transform (BWT) algorithm applied to the sorting procedure of interferometric data, in view of their lossless compression: the Dynamic Segmentation and Sorting (DSS) algorithm. This algorithm is based on the application of the Dynamic Perceptron (DP) neural algorithm. It allows a fast and computationally efficient dynamic segmentation into homogeneous blocks of the coefficients of the Fourier transform. In this way, a limited order sorting procedure of such coefficients can be allowed, optimizing the BWT sorting procedure, characterized as such by an unlimited order. This new method has been specifically studied in order to its hardware implementation for integrating, as a fast compression module, the Micro-Electro-Optical-Mach Zender-Sensor (MEOMS) -- a integrated optical micro-sensor of the MEOS class, based on an array of Mach-Zender type interferometers. This device has been recently designed and constructed in Italy, at the IMM and ISAC Institutes of the Italian National Research Council (CNR) in Bologna. Because of its characteristics, the complete system is suitable for being installed onboard on satellites, for the continuous monitoring of the earth atmosphere. Some encouraging previous results of our lossless compression module of the interferograms outputted by the MEOMS are presented at the end of this paper.

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Gianfranco Basti and Antonio Luigi Perrone "A fast hybrid block-sorting algorithm for lossless interferometric data compression", Proc. SPIE 5103, Intelligent Computing: Theory and Applications, (4 August 2003); https://doi.org/10.1117/12.487504

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