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Open AccessArticle
Dehazing of Panchromatic Remote Sensing Images Based on Histogram Features
by
Hao Wang
Hao Wang 1,2,
Yalin Ding
Yalin Ding 1,2,*,
Xiaoqin Zhou
Xiaoqin Zhou 3,
Guoqin Yuan
Guoqin Yuan 1,2 and
Chao Sun
Chao Sun 1
1
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130012, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2025, 17(20), 3479; https://doi.org/10.3390/rs17203479 (registering DOI)
Submission received: 25 September 2025
/
Revised: 3 October 2025
/
Accepted: 15 October 2025
/
Published: 18 October 2025
Abstract
During long-range imaging, the turbid medium in the atmosphere absorbs and scatters light, resulting in reduced contrast, a narrowed dynamic range, and obscure detail information in remote sensing images. The prior-based method has the advantages of good real-time performance and a wide application range. However, few of the existing prior-based methods are applicable to the dehazing of panchromatic images. In this paper, we innovatively propose a prior-based dehazing method for panchromatic remote sensing images through statistical histogram features. First, the hazy image is divided into plain image patches and mixed image patches according to the histogram features. Then, the features of the average occurrence differences between adjacent gray levels (AODAGs) of plain image patches and the features of the average distance to the gray-level gravity center (ADGG) of mixed image patches are, respectively, calculated. Then, the transmission map is obtained according to the statistical relation equation. Then, the atmospheric light of each image patch is calculated separately based on the maximum gray level of the image patch using the threshold segmentation method. Finally, the dehazed image is obtained based on the physical model. Extensive experiments in synthetic and real-world panchromatic hazy remote sensing images show that the proposed algorithm outperforms state-of-the-art dehazing methods in both efficiency and dehazing effect.
Share and Cite
MDPI and ACS Style
Wang, H.; Ding, Y.; Zhou, X.; Yuan, G.; Sun, C.
Dehazing of Panchromatic Remote Sensing Images Based on Histogram Features. Remote Sens. 2025, 17, 3479.
https://doi.org/10.3390/rs17203479
AMA Style
Wang H, Ding Y, Zhou X, Yuan G, Sun C.
Dehazing of Panchromatic Remote Sensing Images Based on Histogram Features. Remote Sensing. 2025; 17(20):3479.
https://doi.org/10.3390/rs17203479
Chicago/Turabian Style
Wang, Hao, Yalin Ding, Xiaoqin Zhou, Guoqin Yuan, and Chao Sun.
2025. "Dehazing of Panchromatic Remote Sensing Images Based on Histogram Features" Remote Sensing 17, no. 20: 3479.
https://doi.org/10.3390/rs17203479
APA Style
Wang, H., Ding, Y., Zhou, X., Yuan, G., & Sun, C.
(2025). Dehazing of Panchromatic Remote Sensing Images Based on Histogram Features. Remote Sensing, 17(20), 3479.
https://doi.org/10.3390/rs17203479
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