The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Algoritma peningkatan imej berasaskan Retinex hibrid dicadangkan untuk meningkatkan kualiti imej yang ditangkap oleh kenderaan udara tanpa pemandu (UAV) dalam kertas kerja ini. Hiperparameter model Retinex berskala berbilang yang digunakan dengan pemeliharaan kromatik (MSRCP) ditala secara automatik melalui algoritma pengkomputeran evolusi dua fasa. Dalam algoritma pengoptimuman dua fasa, algoritma Rao-2 digunakan untuk melaksanakan carian global dan penyelesaian diperoleh dengan memaksimumkan fungsi objektif. Seterusnya, kaedah Nelder-Mead simplex digunakan untuk menambah baik penyelesaian melalui carian tempatan. Imej sebenar yang diambil UAV dengan kualiti yang tidak baik dikumpul untuk mengesahkan prestasi algoritma yang dicadangkan. Sementara itu, empat algoritma peningkatan imej terkenal, Multi-Scale Retinex, Multi-Scale Retinex dengan Color Restoration, Automated Multi-Scale Retinex, dan MSRCP digunakan sebagai kaedah penanda aras. Sementara itu, dua algoritma pengkomputeran evolusi yang biasa digunakan, pengoptimuman kawanan zarah dan algoritma pendebungaan bunga, dianggap untuk mengesahkan kecekapan kaedah yang dicadangkan dalam penalaan parameter model MSRCP. Keputusan eksperimen menunjukkan bahawa kaedah yang dicadangkan mencapai prestasi terbaik berbanding dengan penanda aras dan dengan itu kaedah yang dicadangkan boleh digunakan untuk aplikasi berasaskan UAV sebenar.
Xinran LIU
University of Science and Technology Beijing,Shunde Graduate School of University of Science and Technology Beijing
Zhongju WANG
University of Science and Technology Beijing,Shunde Graduate School of University of Science and Technology Beijing
Long WANG
University of Science and Technology Beijing,Shunde Graduate School of University of Science and Technology Beijing
Chao HUANG
University of Science and Technology Beijing,Shunde Graduate School of University of Science and Technology Beijing
Xiong LUO
University of Science and Technology Beijing,Shunde Graduate School of University of Science and Technology Beijing
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Salinan
Xinran LIU, Zhongju WANG, Long WANG, Chao HUANG, Xiong LUO, "A Hybrid Retinex-Based Algorithm for UAV-Taken Image Enhancement" in IEICE TRANSACTIONS on Information,
vol. E104-D, no. 11, pp. 2024-2027, November 2021, doi: 10.1587/transinf.2021EDL8050.
Abstract: A hybrid Retinex-based image enhancement algorithm is proposed to improve the quality of images captured by unmanned aerial vehicles (UAVs) in this paper. Hyperparameters of the employed multi-scale Retinex with chromaticity preservation (MSRCP) model are automatically tuned via a two-phase evolutionary computing algorithm. In the two-phase optimization algorithm, the Rao-2 algorithm is applied to performing the global search and a solution is obtained by maximizing the objective function. Next, the Nelder-Mead simplex method is used to improve the solution via local search. Real UAV-taken images of bad quality are collected to verify the performance of the proposed algorithm. Meanwhile, four famous image enhancement algorithms, Multi-Scale Retinex, Multi-Scale Retinex with Color Restoration, Automated Multi-Scale Retinex, and MSRCP are utilized as benchmarking methods. Meanwhile, two commonly used evolutionary computing algorithms, particle swarm optimization and flower pollination algorithm, are considered to verify the efficiency of the proposed method in tuning parameters of the MSRCP model. Experimental results demonstrate that the proposed method achieves the best performance compared with benchmarks and thus the proposed method is applicable for real UAV-based applications.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2021EDL8050/_p
Salinan
@ARTICLE{e104-d_11_2024,
author={Xinran LIU, Zhongju WANG, Long WANG, Chao HUANG, Xiong LUO, },
journal={IEICE TRANSACTIONS on Information},
title={A Hybrid Retinex-Based Algorithm for UAV-Taken Image Enhancement},
year={2021},
volume={E104-D},
number={11},
pages={2024-2027},
abstract={A hybrid Retinex-based image enhancement algorithm is proposed to improve the quality of images captured by unmanned aerial vehicles (UAVs) in this paper. Hyperparameters of the employed multi-scale Retinex with chromaticity preservation (MSRCP) model are automatically tuned via a two-phase evolutionary computing algorithm. In the two-phase optimization algorithm, the Rao-2 algorithm is applied to performing the global search and a solution is obtained by maximizing the objective function. Next, the Nelder-Mead simplex method is used to improve the solution via local search. Real UAV-taken images of bad quality are collected to verify the performance of the proposed algorithm. Meanwhile, four famous image enhancement algorithms, Multi-Scale Retinex, Multi-Scale Retinex with Color Restoration, Automated Multi-Scale Retinex, and MSRCP are utilized as benchmarking methods. Meanwhile, two commonly used evolutionary computing algorithms, particle swarm optimization and flower pollination algorithm, are considered to verify the efficiency of the proposed method in tuning parameters of the MSRCP model. Experimental results demonstrate that the proposed method achieves the best performance compared with benchmarks and thus the proposed method is applicable for real UAV-based applications.},
keywords={},
doi={10.1587/transinf.2021EDL8050},
ISSN={1745-1361},
month={November},}
Salinan
TY - JOUR
TI - A Hybrid Retinex-Based Algorithm for UAV-Taken Image Enhancement
T2 - IEICE TRANSACTIONS on Information
SP - 2024
EP - 2027
AU - Xinran LIU
AU - Zhongju WANG
AU - Long WANG
AU - Chao HUANG
AU - Xiong LUO
PY - 2021
DO - 10.1587/transinf.2021EDL8050
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E104-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2021
AB - A hybrid Retinex-based image enhancement algorithm is proposed to improve the quality of images captured by unmanned aerial vehicles (UAVs) in this paper. Hyperparameters of the employed multi-scale Retinex with chromaticity preservation (MSRCP) model are automatically tuned via a two-phase evolutionary computing algorithm. In the two-phase optimization algorithm, the Rao-2 algorithm is applied to performing the global search and a solution is obtained by maximizing the objective function. Next, the Nelder-Mead simplex method is used to improve the solution via local search. Real UAV-taken images of bad quality are collected to verify the performance of the proposed algorithm. Meanwhile, four famous image enhancement algorithms, Multi-Scale Retinex, Multi-Scale Retinex with Color Restoration, Automated Multi-Scale Retinex, and MSRCP are utilized as benchmarking methods. Meanwhile, two commonly used evolutionary computing algorithms, particle swarm optimization and flower pollination algorithm, are considered to verify the efficiency of the proposed method in tuning parameters of the MSRCP model. Experimental results demonstrate that the proposed method achieves the best performance compared with benchmarks and thus the proposed method is applicable for real UAV-based applications.
ER -