Accuracy Assessment of Haze Removal of SPOT 6/7 Imagery using Haze Index Algorithm Based on Machine Learning Classification

D. Heri Y. Sulyantara; Mulia Inda Rahayu; Kurnia Ulfa; Andie Setiyoko; Orbita Roswintiarti; Sastra Kusuma Wijaya; Abdul Haris

doi:10.1109/ICARES60489.2023.10329912

Accuracy Assessment of Haze Removal of SPOT 6/7 Imagery using Haze Index Algorithm Based on Machine Learning Classification

D. Heri Y. Sulyantara, Mulia Inda Rahayu, Kurnia Ulfa, Andie Setiyoko, Orbita Roswintiarti, Sastra Kusuma Wijaya, Abdul Haris

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Multispectral optical remote sensing imagery in tropical regions such as Indonesia is often suffer from haze and cirrus contamination. This will affect to a reduction in image quality and accuracy of data interpretation. To mitigate these issues, a haze removal method has been developed employing the haze index algorithm which is based on reflectance values of the blue and red channels of SPOT 6/7 imagery. However the method must be tested to find out whether the result is sufficient for further implementation or not. The efficacy of the method was determined by testing the data with image interpretation using machine learning classification method to judge the efficiencies of the haze removal algorithm on SPOT 6/7 imagery. Experimental results indicate that the algorithm is proficient in information extraction using haze-free SPOT 6/7 data that has been processed using this method. As a result, data processed with haze removal based on the haze index technique can be useful for remote sensing applications.

Original language	English
Title of host publication	2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350344004
DOIs	https://doi.org/10.1109/ICARES60489.2023.10329912
Publication status	Published - 2023
Event	2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023 - Hybrid, Bali, Indonesia Duration: 26 Oct 2023 → 27 Oct 2023

Publication series

Name	2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023

Conference

Conference	2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023
Country/Territory	Indonesia
City	Hybrid, Bali
Period	26/10/23 → 27/10/23

Keywords

classification
haze index
haze removal
machine learning
SPOT 6/7

Access to Document

10.1109/ICARES60489.2023.10329912

Cite this

Sulyantara, D. H. Y., Rahayu, M. I., Ulfa, K., Setiyoko, A., Roswintiarti, O., Wijaya, S. K., & Haris, A. (2023). Accuracy Assessment of Haze Removal of SPOT 6/7 Imagery using Haze Index Algorithm Based on Machine Learning Classification. In 2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023 (2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICARES60489.2023.10329912

Sulyantara, D. Heri Y. ; Rahayu, Mulia Inda ; Ulfa, Kurnia et al. / Accuracy Assessment of Haze Removal of SPOT 6/7 Imagery using Haze Index Algorithm Based on Machine Learning Classification. 2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023).

@inproceedings{008a1f02281a439c943cd7cbedd23204,

title = "Accuracy Assessment of Haze Removal of SPOT 6/7 Imagery using Haze Index Algorithm Based on Machine Learning Classification",

abstract = "Multispectral optical remote sensing imagery in tropical regions such as Indonesia is often suffer from haze and cirrus contamination. This will affect to a reduction in image quality and accuracy of data interpretation. To mitigate these issues, a haze removal method has been developed employing the haze index algorithm which is based on reflectance values of the blue and red channels of SPOT 6/7 imagery. However the method must be tested to find out whether the result is sufficient for further implementation or not. The efficacy of the method was determined by testing the data with image interpretation using machine learning classification method to judge the efficiencies of the haze removal algorithm on SPOT 6/7 imagery. Experimental results indicate that the algorithm is proficient in information extraction using haze-free SPOT 6/7 data that has been processed using this method. As a result, data processed with haze removal based on the haze index technique can be useful for remote sensing applications.",

keywords = "classification, haze index, haze removal, machine learning, SPOT 6/7",

author = "Sulyantara, {D. Heri Y.} and Rahayu, {Mulia Inda} and Kurnia Ulfa and Andie Setiyoko and Orbita Roswintiarti and Wijaya, {Sastra Kusuma} and Abdul Haris",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023 ; Conference date: 26-10-2023 Through 27-10-2023",

year = "2023",

doi = "10.1109/ICARES60489.2023.10329912",

language = "English",

series = "2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023",

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Sulyantara, DHY, Rahayu, MI, Ulfa, K, Setiyoko, A, Roswintiarti, O, Wijaya, SK & Haris, A 2023, Accuracy Assessment of Haze Removal of SPOT 6/7 Imagery using Haze Index Algorithm Based on Machine Learning Classification. in 2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023. 2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023, Hybrid, Bali, Indonesia, 26/10/23. https://doi.org/10.1109/ICARES60489.2023.10329912

Accuracy Assessment of Haze Removal of SPOT 6/7 Imagery using Haze Index Algorithm Based on Machine Learning Classification. / Sulyantara, D. Heri Y.; Rahayu, Mulia Inda; Ulfa, Kurnia et al.
2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Accuracy Assessment of Haze Removal of SPOT 6/7 Imagery using Haze Index Algorithm Based on Machine Learning Classification

AU - Sulyantara, D. Heri Y.

AU - Rahayu, Mulia Inda

AU - Ulfa, Kurnia

AU - Setiyoko, Andie

AU - Roswintiarti, Orbita

AU - Wijaya, Sastra Kusuma

AU - Haris, Abdul

PY - 2023

Y1 - 2023

N2 - Multispectral optical remote sensing imagery in tropical regions such as Indonesia is often suffer from haze and cirrus contamination. This will affect to a reduction in image quality and accuracy of data interpretation. To mitigate these issues, a haze removal method has been developed employing the haze index algorithm which is based on reflectance values of the blue and red channels of SPOT 6/7 imagery. However the method must be tested to find out whether the result is sufficient for further implementation or not. The efficacy of the method was determined by testing the data with image interpretation using machine learning classification method to judge the efficiencies of the haze removal algorithm on SPOT 6/7 imagery. Experimental results indicate that the algorithm is proficient in information extraction using haze-free SPOT 6/7 data that has been processed using this method. As a result, data processed with haze removal based on the haze index technique can be useful for remote sensing applications.

AB - Multispectral optical remote sensing imagery in tropical regions such as Indonesia is often suffer from haze and cirrus contamination. This will affect to a reduction in image quality and accuracy of data interpretation. To mitigate these issues, a haze removal method has been developed employing the haze index algorithm which is based on reflectance values of the blue and red channels of SPOT 6/7 imagery. However the method must be tested to find out whether the result is sufficient for further implementation or not. The efficacy of the method was determined by testing the data with image interpretation using machine learning classification method to judge the efficiencies of the haze removal algorithm on SPOT 6/7 imagery. Experimental results indicate that the algorithm is proficient in information extraction using haze-free SPOT 6/7 data that has been processed using this method. As a result, data processed with haze removal based on the haze index technique can be useful for remote sensing applications.

KW - classification

KW - haze index

KW - haze removal

KW - machine learning

KW - SPOT 6/7

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M3 - Conference contribution

AN - SCOPUS:85180541665

T3 - 2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023

BT - 2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023

Y2 - 26 October 2023 through 27 October 2023

ER -

Sulyantara DHY, Rahayu MI, Ulfa K, Setiyoko A, Roswintiarti O, Wijaya SK et al. Accuracy Assessment of Haze Removal of SPOT 6/7 Imagery using Haze Index Algorithm Based on Machine Learning Classification. In 2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2023). doi: 10.1109/ICARES60489.2023.10329912

Accuracy Assessment of Haze Removal of SPOT 6/7 Imagery using Haze Index Algorithm Based on Machine Learning Classification

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