TY - JOUR
T1 - Object Detection in Hyperspectral Images
AU - Yan, Longbin
AU - Zhao, Min
AU - Wang, Xiuheng
AU - Zhang, Yuge
AU - Chen, Jie
N1 - Publisher Copyright:
© 1994-2012 IEEE.
PY - 2021
Y1 - 2021
N2 - High spectral resolution of hyperspectral images allows the detection and classification of materials in the observed images. However, existing research on hyperspectral detection mainly focuses on pixel-level study, partially due to the low spatial resolution in typical earth observation applications. With the development of imaging techniques, high-spatial-resolution hyperspectral data can be obtained and object-level detection is necessary for many applications. In this work, the object-based hyperspectral detection problem is formulated, and a convolutional neural network is then designed based on the specific characteristics of this problem. Moreover, a hyperspectral dataset with over 400 high-quality images for object-level target detection is created. Experimental results validate the proposed framework and show its superior performance.
AB - High spectral resolution of hyperspectral images allows the detection and classification of materials in the observed images. However, existing research on hyperspectral detection mainly focuses on pixel-level study, partially due to the low spatial resolution in typical earth observation applications. With the development of imaging techniques, high-spatial-resolution hyperspectral data can be obtained and object-level detection is necessary for many applications. In this work, the object-based hyperspectral detection problem is formulated, and a convolutional neural network is then designed based on the specific characteristics of this problem. Moreover, a hyperspectral dataset with over 400 high-quality images for object-level target detection is created. Experimental results validate the proposed framework and show its superior performance.
KW - Hyperspectral imaging
KW - convolutional neural network
KW - object-based detection
KW - target detection
UR - http://www.scopus.com/inward/record.url?scp=85100919489&partnerID=8YFLogxK
U2 - 10.1109/LSP.2021.3059204
DO - 10.1109/LSP.2021.3059204
M3 - 文章
AN - SCOPUS:85100919489
SN - 1070-9908
VL - 28
SP - 508
EP - 512
JO - IEEE Signal Processing Letters
JF - IEEE Signal Processing Letters
M1 - 9354961
ER -