International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Image Dehazing Using Machine Learning Algoithms

Abstract

Image dehazing is a crucial preprocessing step in computer vision applications, as haze and fog significantly degrade image quality and reduce visibility. This project explores the use of machine learning algorithms to enhance image clarity by removing haze effects. Various supervised and unsupervised learning techniques are applied to improve contrast, restore lost details, and optimize computational efficiency. The proposed system leverages convolutional neural networks (CNNs) and regression-based models to predict haze density and reconstruct clear images. Experimental results demonstrate improved performance compared to traditional dehazing methods. The project contributes to real-world applications such as autonomous driving, surveillance, and remote sensing. (Times New Roman, Size 10, ≤250 words, Justified).

Country : India

1 Gauri Khandve2 Krutika Shinde3 Siddhi Patil4 Apurva Sathe5 Prof. Sumoli Vaje6 Prof. Nita Pawar

  1. Student, Computer Engineering Diploma, Ajeenkya D. Y. Patil School of Engineering, Charholi, Pune, India
  2. Student, Computer Engineering Diploma, Ajeenkya D. Y. Patil School of Engineering, Charholi, Pune, India
  3. Student, Computer Engineering Diploma, Ajeenkya D. Y. Patil School of Engineering, Charholi, Pune, India
  4. Student, Computer Engineering Diploma, Ajeenkya D. Y. Patil School of Engineering, Charholi, Pune, India
  5. Guide, Professor, Computer Engineering Diploma, Ajeenkya D. Y. Patil School of Engineering, Charholi, Pune, India
  6. HOD, Professor, Computer Engineering Diploma, Ajeenkya D. Y. Patil School of Engineering, Charholi, Pune, India

IRJIET, Volume 9, Issue 12, December 2025 pp. 154-157

doi.org/10.47001/IRJIET/2025.912023

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References

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