Large-scale hyperspectral image compression via sparse representations based on online learning Cover

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Large-scale hyperspectral image compression via sparse representations based on online learning

International Journal of Applied Mathematics and Computer Science

Volume 28 (2018): Issue 1 (March 2018)

By: İrem Ülkü and Ersin Kizgut

Open Access

|Mar 2018

Authors

İrem Ülkü

iremulku@cankaya.edu.tr

Department of Electrical and Electronics Engineering Çankaya University, Eskişehir Yolu 29.km, 06790, Ankara, Turkey

Ersin Kizgut

University Institute of Pure and Applied Mathematics (IUMPA) Technical University of Valencia, E-46071, Valencia, Spain

DOI: https://doi.org/10.2478/amcs-2018-0015 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X

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Language: English

Page range: 197 - 207

Submitted on: Feb 10, 2017

|

Accepted on: Oct 16, 2017

|

Published on: Mar 31, 2018

Published by: University of Zielona Góra

In partnership with: Paradigm Publishing Services

Publication frequency: 4 issues per year

Keywords:

hyperspectral imaging,

compression algorithms,

dictionary learning,

Related subjects:

Applied mathematics

© 2018 İrem Ülkü, Ersin Kizgut, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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