TY - GEN
T1 - Examining Change Detection Methods for Hyperspectral Data
AU - Radomsky, Barak
AU - Daniel, Adi
AU - Rotman, Stanley R.
N1 - Publisher Copyright: © 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - The requirement for change detection in hyperspectral data appears to be an important and necessary tool in a variety of fields such as military, medical, geology, etc. The main objective of change detection is to observe changes of the probability distribution of a stochastic process. In this paper, we analyze two detection methods which were introduced by Schaum Stocker: chronochrome and covariance equalization. We observe the viability of both methods for when there is misregistration between the images and determine which one is better than the other at finding anomalies.
AB - The requirement for change detection in hyperspectral data appears to be an important and necessary tool in a variety of fields such as military, medical, geology, etc. The main objective of change detection is to observe changes of the probability distribution of a stochastic process. In this paper, we analyze two detection methods which were introduced by Schaum Stocker: chronochrome and covariance equalization. We observe the viability of both methods for when there is misregistration between the images and determine which one is better than the other at finding anomalies.
KW - Chronochrome
KW - Covariance equalization
KW - Hyperspectral imaging
KW - Target detection
UR - http://www.scopus.com/inward/record.url?scp=85063160786&partnerID=8YFLogxK
U2 - 10.1109/ICSEE.2018.8646175
DO - 10.1109/ICSEE.2018.8646175
M3 - Conference contribution
T3 - 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018
BT - 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018
T2 - 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018
Y2 - 12 December 2018 through 14 December 2018
ER -