Skip to Main Content
 

Global Search Box

 
 
 
 

Files

File List


Durkee_thesis_draft.pdf (5.2 MB)

ETD Abstract Container

Abstract Header

Temperature Robust Longwave Infrared Hyperspectral Change Detection

Durkee, Nicholas A.
http://orcid.org/0000-0003-2929-2206
http://rave.ohiolink.edu/etdc/view?acc_num=wright1547481549821121

Abstract Details

2018, Master of Science in Electrical Engineering (MSEE), Wright State University, Electrical Engineering.
In this thesis, we develop and evaluate change detection algorithms for longwave infrared (LWIR) hyperspectral imagery. Because measured radiance in the LWIR domain depends on unknown surface temperature, care must be taken to prevent false alarms resulting from in-scene temperature differences that appear as material changes. We consider four strategies to mitigate this effect. In the first, pre-processing via traditional temperatureemissivity separation yields approximately temperature-invariant emissivity vectors for use in change detection. In the second, we utilize alpha residuals to obtain robustness to temperature errors. Next, we adopt a minimax approach that minimizes the maximal spectral deviation between measurements. Finally, we reduce our minmax approach to solve with fewer variables. Examples using synthetic and measured data quantify the computational complexity of the proposed methods and demonstrate orders of magnitude reduction in false alarm rates relative to existing methods.
Joshua Ash, Ph.D. (Advisor)
Fred Garber, Ph.D. (Committee Member)
Arnab Shaw, Ph.D. (Committee Member)
97 p.
Electrical Engineering
Signal processing; Hyperspectral; Change detection; Longwave; Optimization; smoothness-TES; alpha residuals; alpha emissivity; orthogonal projection

Recommended Citations

Citations

  • Durkee, N. A. (2018). Temperature Robust Longwave Infrared Hyperspectral Change Detection [Master's thesis, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright1547481549821121

    APA Style (7th edition)

  • Durkee, Nicholas. Temperature Robust Longwave Infrared Hyperspectral Change Detection. 2018. Wright State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=wright1547481549821121.

    MLA Style (8th edition)

  • Durkee, Nicholas. "Temperature Robust Longwave Infrared Hyperspectral Change Detection." Master's thesis, Wright State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=wright1547481549821121

    Chicago Manual of Style (17th edition)

wright1547481549821121
10,121
© 2018, some rights reserved.Creative Commons License Temperature Robust Longwave Infrared Hyperspectral Change Detection by Nicholas A. Durkee is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by Wright State University and OhioLINK.