Iterative Enhanced Multivariance Products Representation for Effective Compression of Hyperspectral Images

Informatics Institute faculty members Prof. Dr. Metin Demiralp and Assoc. Dr. Behçet Uğur Töreyi coauthored paper titled “Iterative Enhanced Multivariance Products Representation for Effective Compression of Hyperspectral Images' has been published in IEEE Transactions on Geoscience and Remote Sensing on 2020/11/16.

Abstract:

Effective compression of hyperspectral (HS) images is essential due to their large data volume. Since these images are high dimensional, processing them is also another challenging issue. In this work, an efficient lossy HS image compression method based on enhanced multivariance products representation (EMPR) is proposed. As an efficient data decomposition method, EMPR enables us to represent the given multidimensional data with lower-dimensional entities. EMPR, as a finite expansion with relevant approximations, can be acquired by truncating this expansion at certain levels. Thus, EMPR can be utilized as a highly effective lossy compression algorithm for hyper spectral images. In addition to these, an efficient variety of EMPR is also introduced in this article, in order to increase the compression efficiency. The results are benchmarked with several state-of-the-art lossy compression methods. It is observed that both higher peak signal-to-noise ratio values and improved classification accuracy are achieved from EMPR-based methods.

Date 22 Dec 2020

ITU Informatics Institute provides graduate-level education and research in applied informatics, computer sciences, computational science and engineering, communication systems under the following programs.

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Faculty members and students conduct research supported by national and international organızatıons in the fields of electromagnetic fields, communication systems/regulations, computational materials design, computational chemistry/biology, cryptography, signal/data processing/visualization, big data management, climate and ocean sciences,

The paper titled “Non-Invasive Complete Hemodynamic Model to Investigate the Effect of Multi-Stenosis in Patient-Specific Coronary Arteries”, jointly prepared by research assistants Hacer Duzman and E. Cenk Ersan, andProf. Dr. M. Serdar Çelebi from the Computational Science and Engineering Program, has been awarded the Best Paper Award at the ESM’25. (22-24 Oct. 2025 Belgium)
Hacer Duzman and Muhammed Enis Şen, PhD students of Computational Science and Engineering Program, received awards in the "5 Minute Thesis Competition" organized at the "Başarım 2024 8th National High Performance Computing Conference".

There is also a High Performance Computing Laboratory established with the support of the State Planning Organization within the Institute.

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