HAZE REMOVAL SYSTEM USING IMAGE PROCESSING

Authors

  • Dr. Sumitha Manoj
  • Anusha S Gowda
  • Chaitra S
  • Likitha Y

Keywords:

transmission map. Dehaze, defog, picture reclamation, profundity estimation.

Abstract

Cloudiness evacuation for a solitary picture is comprehended to be a difficult poorly presented issue in PC vision. The exhibition of past picture dehazing technique is confined by the convenience of hand-structured highlights. Cloudiness is one among the preeminent significant elements which decrease the outside picture quality. Leaving approaches regularly plan to style their models bolstered standards of fogs. During this paper, we propose a simple yet compelling picture earlier channel before expel dimness from one info picture. The dim channel earlier might be a very measurement of outside dimness free pictures. Its bolstered a key perception most neighborhood fixes in open air dimness free pictures contain a few pixels whose power is unbelievably low in at least one shading channel. Utilizing this earlier with the cloudiness imaging model, we can straightforwardly assess the thickness of the dimness and recoup a top notch fog free picture. Results on an assortment of dim pictures show the intensity of the proposed earlier.

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References

Cheng-Hsiung Hsieh, Shih-Cheng Horng, Zen-Jun Huang and Qiangfu Zhao ―Objective Haze Removal Assessment Based on Two-Objective Optimization‖, 2017 IEEE 8th International Conference on Awareness Science and Technology (ICAST2017).

Risheng Liu, Shiqi Li, Long Ma, Xin Fan, Haojie Li, Zhongxuan Luo, ―Robust Haze Removal Via Joint Deep Transmission and Scene Propagation‖, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing(ICASSP).

Fein Dai, Baojie Fan, Yan Peng, ―An image haze removal algorithm based on block wise processing using LAB color space and bilateral filtering‖, 2018 Chinese Control and Decision Conference(CCDC),

Kaiming He, Jian Sun, and Xiaoou Tang, ―Single Image Haze Removal Using Dark Channel Prior‖, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 33, No. 12, December 2011, pp2341-2353.

R. Tan, ―Visibility in Bad Weather from a Single Image,‖ Proc. IEEE Conf. Computer Vision and Pattern Recognition, June2008.

A. Levin, D. Lischinski, and Y. Weiss, ―A Closed Form Solution to Natural Image Matting,‖ Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 61- 68,2006.

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Published

2021-06-30

How to Cite

Manoj, D. S. ., Gowda, A. S. ., S, C. ., & Y, L. . (2021). HAZE REMOVAL SYSTEM USING IMAGE PROCESSING. The Journal of Contemporary Issues in Business and Government, 27(3), 1731–1740. Retrieved from https://cibgp.com/au/index.php/1323-6903/article/view/1783

Issue

Vol. 27 No. 3 (2021): The journal of contemporary issues in business and government

Section

Articles

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