ICTACT Journal on Image and Video Processing

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

A Review on Comparative Analysis of Dehazing of Remote Sensing Images using Different Filters


Affiliations
1 Department of Electronics and Communication Engineering, Government College of Technology, India
     

   Subscribe/Renew Journal


Haze is an atmospheric phenomenon caused by scattering of atmospheric particles in air and these factor causes deterioration of images, captured by the sensors. Haze detection, removal and enhancement of dehazed images are extremely important for the analysis and interpretation of Remote sensing images. This work presents the comparison of haze removal methodologies and analysis of dehazed images in terms of its image quality metrics. Consequently various imaging filters are employed to enhance fine details in the dehazed images and comparative analysis is presented. Simulation results reveal that the filter enhancement technique produces images with better quality and visible improvements in Quality metrics.

Keywords

Remote Sensing, Haze Removal, Adaptive Dehazing, Deformed Haze Imaging Model, Dark Channel Prior, Dark Channel Saturation Prior, Image Filters.
Subscription Login to verify subscription
User
Notifications
Font Size

  • Bin Xie and Zixing Cai, “Improved Single Image Dehazing using Dark Channel Prior and Multiscale Retinex”, Proceedings of International Conference on Intelligent System and Engineering Application, pp. 848-851, 2010.

  • Feng Liu and Canmei Yang, “A Fast method for Single image dehazing using Dark Channel Prior”, Proceedings of IEEE International Conference on Signal processing, Communications and Computing, pp. 483-486, 2014.

  • Fengying Xie, Jiajie Chen, Xiaxoxi Pan and Zhiguo Jiang, “Adaptive Haze Removal for Single Remote Sensing Image”, IEEE Access, Vol. 6, pp. 67982-67991, 2018.

  • Kamining He, Jian Sun, Xiaoou Tang, “Single Image Haze Removal using Dark Channel Prior”, IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 33, No. 12, pp. 2341-2353, 2011.

  • Kamining He, Jian Sun and Xiaoou Tang, “Guided Imaging Filter”, IEEE Transactions on Software Engineering, Vol. 35, No. 6, pp. 1397-1409, 2013.

  • Le Thi Thanh, Dang N.H. Thanh, Nguyen Minh Hue and V.B. Surya Prasath, “Single Image dehazing based on Adaptive Histogram Equalization and Linearization of Gamma Correction”, Proceedings of Asia-Pacific Conference on Communications, pp. 36-40, 2019.

  • Mohammed Mahmood Ali, M.D. Ateeq Ur Rahman and Shaikha Hajira, “A Comparative Study of Various Dehazing Techniques”, Proceedings of International Conference on Energy, Communication, Data Analytics and Soft Computing, pp.3622-3628, 2017.

  • Rizal Mutaqin, Fresy Nugraho and Nugraha Gumilar, “Increasing Dehazing Process using Fast Guided filter on Dark Channel Prior”, Proceedings of International Conference on Electrical, Electronics and Information Engineering, pp. 77-82, 2017.

  • Xiaoxi Pan, Fengying Xie, Zhiguo Jiang and Jihao Yin, “Haze Removal for a Single Remote Sensing Image Based on Deformed Haze Imaging Model”, IEEE Signal Processing Letters, Vol. 22, No. 10, pp. 1806-1810, 2015.

  • Xiaxoxi Pan, Fengying Xie, Zhiguo Jiang, Zhenwei Shi and Xiaoyan Luo, “No Reference Assessment on Haze for Remote Sensing Images”, IEEE Geoscience and Remote Sensing Letters, Vol. 13, No. 12, pp. 1855-1859, 2016.

  • Xueyang Fu, Jiye Wang, Delu Zeng, Yue Huang, Xinghao Ding, “Remote Sensing Image Enhancement using Regularized-Histogram Equalization and DCT”, IEEE Geo Science and Remote Sensing Letters, Vol. 12, No. 11, pp. 2301-2305, 2015.

  • Yan Wang and Bo Wu, “Improved Single Image Dehazing using Dark Channel Prior”, Proceedings of International Conference on Intelligent Computing and Intelligent System, pp. 789-792, 2010.

  • Yuling Chen, Zhan Li, Bir Bhanu, Daofa tang, Qingyu Peng and Qingfeng Zha, “Improving Transmission by Designing Filters for image Dehazing”, Proceedings of International Conference on Image Vision and Computing, pp. 374-378, 2018.


Abstract Views: 333

PDF Views: 0




  • A Review on Comparative Analysis of Dehazing of Remote Sensing Images using Different Filters

Abstract Views: 333  |  PDF Views: 0

Authors

M. Kamalam
Department of Electronics and Communication Engineering, Government College of Technology, India
N. Ameena Bibi
Department of Electronics and Communication Engineering, Government College of Technology, India

Abstract


Haze is an atmospheric phenomenon caused by scattering of atmospheric particles in air and these factor causes deterioration of images, captured by the sensors. Haze detection, removal and enhancement of dehazed images are extremely important for the analysis and interpretation of Remote sensing images. This work presents the comparison of haze removal methodologies and analysis of dehazed images in terms of its image quality metrics. Consequently various imaging filters are employed to enhance fine details in the dehazed images and comparative analysis is presented. Simulation results reveal that the filter enhancement technique produces images with better quality and visible improvements in Quality metrics.

Keywords


Remote Sensing, Haze Removal, Adaptive Dehazing, Deformed Haze Imaging Model, Dark Channel Prior, Dark Channel Saturation Prior, Image Filters.

References