Publisher of Iranian Journals and Conference Proceedings

Please waite ..
Publisher of Iranian Journals and Conference Proceedings
Login |Register |Help |عضویت کتابخانه ها
Paper
Title

Hyperspectral Data Unmixing Using Constrained Semi-NMF and PCA Transform

Year: 1391
COI: ICEE20_596
Language: EnglishView: 892
This Paper With 5 Page And PDF Format Ready To Download

Buy and Download

با استفاده از پرداخت اینترنتی بسیار سریع و ساده می توانید اصل این Paper را که دارای 5 صفحه است به صورت فایل PDF در اختیار داشته باشید.
آدرس ایمیل خود را در کادر زیر وارد نمایید:

Authors

Habib Alizadeh - Faculty of Electrical and Computer Engineering, Tarbiat Modares University
Hassan Ghassemian

Abstract:

One of problems that have been not considered in unmixing process of hyperspectral is the correlation between bands. This correlation makes difficult the unmixing of spectralsignatures of different materials. Furthermore, the large number of spectral bands extends the execution time of the unmixing process. In this paper, a new approach for the unmixing of hyperspectral data using the semi-Nonnegative Matrix Factor (semi-NMF) and Principal Component Analysis (PCA) isproposed that solves the problem of correlation between bands and decrease execution time of algorithm. The proposedapproach uses from PCA of data in the unmixing process instead of original data. Using this linear transformation, the images are mapped to the uncorrelated space. Uncorrelated images make more efficient the unmixing process. In order to overcome the problem of non-uniqueness solution that is caused by the nonconvex cost function, the smoothness and sparseness constraints are introduced to the semi-NMF. In addition to its high accuracy, the proposed method increases the speed of the unmixing process. The experimental results show excellence of the proposed approach in comparison of other methods

Keywords:

Hyperspectral images , Hyperspectral data unmixing , semi-Nonnegative Matrix Factorization (semi-NMF) , Principal Component Analysis (PCA)

Paper COI Code

This Paper COI Code is ICEE20_596. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/154804/

How to Cite to This Paper:

If you want to refer to this Paper in your research work, you can simply use the following phrase in the resources section:
Alizadeh, Habib and Ghassemian, Hassan,1391,Hyperspectral Data Unmixing Using Constrained Semi-NMF and PCA Transform,20th Iranian Conference on Electric Engineering,Tehran,https://civilica.com/doc/154804

مراجع و منابع این Paper:

لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :

  • J. M. Nascimento, J. M. Dias, "Vertex Component Analysis: A ...
  • _ Qian, _ matrix factorizatio forhyperspectral unmixing, " IEEE Trans. ...
  • Cichocki, R. Zdunek, A. Huy Phan, S. Amari, "Nomnegative Matrix ...
  • Ann Arbor, MI 1971, pp. 1307-1320. ...
  • X. Liu, W. Xia, B. Wang, L. Zhang, Senior, _ ...
  • _ _ _ Computer Technology and Development, pp.165-168. ...
  • V. Paul Pauca, J. Piper, Robert J. Plemmons, "Nonnegative matrix ...
  • N. Keshava, J. Mustard, "Spectral unmixing, " IEEE Signal Proc. ...

Research Info Management

Certificate | Report | من نویسنده این مقاله هستم

اطلاعات استنادی این Paper را به نرم افزارهای مدیریت اطلاعات علمی و استنادی ارسال نمایید و در تحقیقات خود از آن استفاده نمایید.

Scientometrics

The specifications of the publisher center of this Paper are as follows:
Type of center: دانشگاه دولتی
Paper count: 35,198
In the scientometrics section of CIVILICA, you can see the scientific ranking of the Iranian academic and research centers based on the statistics of indexed articles.

New Papers

New Researchs

Share this page

More information about COI

COI stands for "CIVILICA Object Identifier". COI is the unique code assigned to articles of Iranian conferences and journals when indexing on the CIVILICA citation database.

The COI is the national code of documents indexed in CIVILICA and is a unique and permanent code. it can always be cited and tracked and assumed as registration confirmation ID.

Support