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Efficiently storing and accessing high-resolution solar images using light weight compression techniques

Manjunath, Apoorva Thimlapura (2021) Efficiently storing and accessing high-resolution solar images using light weight compression techniques. Master's, TU Ilmenau.

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Abstract

This thesis is focused on implementing lightweight compression techniques for efficiently storing and accessing high-resolution solar images obtained from Solar Dynamics Observatory. The solar images utilized in this thesis have two-dimensional image data. The value distribution across multiple images is investigated. Images of a different wavelength are likewise subjected to this examination. Dictionary encoding is used as the basic compression layer to compress solar images from AIA for all ten solar wavelengths. Encoding schemes such as Sparse encoding, Run-length Encoding and Coding techniques such as Elias Gamma, Elias Delta and Fibonacci coding are applied as the second layer of compression. A collection of images are stacked to form a multidimensional data cube which is cut into n slices. The compression is applied individually on each of these slices. The evaluation is performed separately on images of various wavelengths, and the compression and decompression outcomes are evaluated independently. The algorithm performance on compressing the images is measured with compression ratio. Various Decompression operations, such as extracting a single slice of a specific image from the cube or extracting a range of slices of multiple images etc., are implemented, and performance of decompression is measured in time.

Item URL in elib:https://elib.dlr.de/148319/
Document Type:Thesis (Master's)
Title:Efficiently storing and accessing high-resolution solar images using light weight compression techniques
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Manjunath, Apoorva ThimlapuraUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date:19 December 2021
Refereed publication:No
Open Access:No
Number of Pages:82
Status:Unpublished
Keywords:data compression, solar images, sdo, data cubes
Institution:TU Ilmenau
Department:Fakultät Informatik und Automatisierung
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - New Data Management Techniques for Earth Observation
Location: Jena
Institutes and Institutions:Institute of Data Science > Datamangagement and Analysis
Deposited By: Paradies, Dr.-Ing. Marcus
Deposited On:17 Jan 2022 09:23
Last Modified:17 Jan 2022 09:23

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