A fast hyperspectral subpixel mapping algorithm based on MAP-TV framework

Zhongkai Hu, Kun Gao, Zeyang Dou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The subpixel mapping technique can obtain a fine-resolution map of target classes in the hyperspectral remote sensing image based on the spatial dependence. In recent years, the subpixel mapping methods based on Maximum A Posterior framework and Total Variation prior (MAP-TV) has received extensive attention because of its unified framework. However, due to the inherent nonlinearity of the TV prior, the traditional gradient descent algorithm to minimize MAP-TV model is inefficient. In this paper, we propose a fast algorithm to solve the MAP-TV model, which combined the fast iterative shrinkage thresholding algorithm and split Bregman algorithm together. The proposed algorithm split the original problem into several sub-problems, each sub-problem has the closed-form solution and is fast to compute. The numerical experiments reveal that the proposed algorithm is faster than the traditional methods and is suitable for the hyperspectral subpixel mapping applications.

Original languageEnglish
Title of host publicationRSIP 2017 - International Workshop on Remote Sensing with Intelligent Processing, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538619902
DOIs
Publication statusPublished - 23 Jun 2017
Event2017 International Workshop on Remote Sensing with Intelligent Processing, RSIP 2017 - Shanghai, China
Duration: 19 May 201721 May 2017

Publication series

NameRSIP 2017 - International Workshop on Remote Sensing with Intelligent Processing, Proceedings

Conference

Conference2017 International Workshop on Remote Sensing with Intelligent Processing, RSIP 2017
Country/TerritoryChina
CityShanghai
Period19/05/1721/05/17

Keywords

  • Maximum a Posterior
  • fast iterative shrinkage thresholding algorithm
  • gradient descent
  • split Bregman algorithm
  • subpixel mapping
  • total variation

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Hu, Z., Gao, K., & Dou, Z. (2017). A fast hyperspectral subpixel mapping algorithm based on MAP-TV framework. In RSIP 2017 - International Workshop on Remote Sensing with Intelligent Processing, Proceedings Article 7958809 (RSIP 2017 - International Workshop on Remote Sensing with Intelligent Processing, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RSIP.2017.7958809