TY - GEN
T1 - Comparative Study on Hyperspectral Image Enhancement for Low Illumination Outdoor Scenes Images
AU - Quan, Lee Yong
AU - Karim, Rohana Abdul
AU - Arshad, Nurul Wahidah
AU - Zakaria, Nor Farizan
AU - Samsudin, Wan Nur Azhani Binti W.
AU - Wahab, Yasmin Abdul
AU - Saputro, Adhi Harmoko
N1 - Funding Information:
We would like to acknowledge funding from Universiti Malaysia Pahang (RDU200323). The authors also would like to thank Faculty of Electrical and Electronics Engineering Technology, Universiti Malaysia Pahang for financial support.
Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2022
Y1 - 2022
N2 - Hyperspectral image is rich with information because it contains spatial and spectral properties of specific objects. However, the image quality may be affected by low lighting conditions caused by non-uniform illumination environments, uncontrollable weather, which tends to darken outdoor scenes. Difficulty arises for high order image processing modalities such as detection, classification and tracking. In this paper, a comparative study was conducted to identify the most appropriate enhancement method for outdoor scenes. Four techniques were investigated: Bio-Inspired Multi-Exposure Fusion (BIMEF), Dehazing, Illumination Estimation, and Multi-deviation Fusion (MF). Experiments revealed that BIMEF is the best approach with the lowest lightness of error.
AB - Hyperspectral image is rich with information because it contains spatial and spectral properties of specific objects. However, the image quality may be affected by low lighting conditions caused by non-uniform illumination environments, uncontrollable weather, which tends to darken outdoor scenes. Difficulty arises for high order image processing modalities such as detection, classification and tracking. In this paper, a comparative study was conducted to identify the most appropriate enhancement method for outdoor scenes. Four techniques were investigated: Bio-Inspired Multi-Exposure Fusion (BIMEF), Dehazing, Illumination Estimation, and Multi-deviation Fusion (MF). Experiments revealed that BIMEF is the best approach with the lowest lightness of error.
KW - Enhancement
KW - Hyperspectral
KW - Low illumination
UR - http://www.scopus.com/inward/record.url?scp=85126966045&partnerID=8YFLogxK
U2 - 10.1007/978-981-16-8690-0_68
DO - 10.1007/978-981-16-8690-0_68
M3 - Conference contribution
AN - SCOPUS:85126966045
SN - 9789811686894
T3 - Lecture Notes in Electrical Engineering
SP - 773
EP - 784
BT - Proceedings of the 6th International Conference on Electrical, Control and Computer Engineering, InECCE 2021
A2 - Md. Zain, Zainah
A2 - Sulaiman, Mohd. Herwan
A2 - Mohamed, Amir Izzani
A2 - Bakar, Mohd. Shafie
A2 - Ramli, Mohd. Syakirin
PB - Springer Science and Business Media Deutschland GmbH
T2 - 6th International Conference on Electrical, Control and Computer Engineering, InECCE 2021
Y2 - 23 August 2021 through 23 August 2021
ER -