Asniyani Nur Haidar Abdullah, Mohd Shafry Mohd Rahim, Sim Hiew Moi, Azah Kamilah Draman, Ahmad Hoirul Basori, Novanto Yudistira
Haze severely degrades image quality by reducing contrast, obscuring details, and introducing a blue-shift color cast caused by atmospheric scattering. Traditional dehazing methods, including prior-based approaches (e.g., DCP, CAP, LPMinVP) and preprocessing techniques (e.g., ICAP WB, Dynamic Gamma), improve visibility but fail to correct haze-induced color imbalance, resulting in unstable RGB distributions and unnatural tone reproduction. This study proposes the Haze-Compensated Color Von Kries (HCCVK) method, a lightweight and training-free preprocessing strategy that performs color compensation before transmission estimation in single-image dehazing. HCCVK integrates a novel red-channel compensation mechanism with Von Kries chromatic adaptation to mitigate wavelength-dependent haze suppression and stabilize chromatic consistency under varying illumination. Unlike learning-based color correction approaches, HCCVK does not require training data, is computationally efficient, and maintains algorithmic interpretability, making it suitable for practical deployment. The method was evaluated on six benchmark datasets: CHIC, Dense-Haze, I-Haze, O-Haze, SOT, and NH-Haze, covering indoor, outdoor, dense, and non-homogeneous haze scenarios. Experimental results based on the RGB color balance metric (σRGB) show that HCCVK reduces color deviation by approximately 75–92% on CHIC, 80–90% on Dense-Haze, and 82–90% on NH-Haze compared to the widely used DCP, and also outperforms CAP, ICAP WB, Dynamic Gamma, and LPMinVP by producing more compact and stable RGB distributions. These findings demonstrate that HCCVK effectively corrects blue-shift imbalance, preserves luminance consistency, and enhances the color stability of dehazing pipelines. © (2025), (Science and Information Organization). All rights reserved.
Pervasive Computing & Educational Technology, Center for Advanced Computing Technology (C-ACT), Department of Media Interactive-Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Melaka, Malaysia; Department of Emergent Computing-Faculty of Computing, Universiti Teknologi Malaysia, UTM Johor Bahru, Johor, 81310, Malaysia; Department of Software Engineering-Faculty of Computing, Universiti Teknologi Malaysia, UTM Johor Bahru, Johor, 81310, Malaysia; Department of Software Engineering, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Melaka, Malaysia; Department of Information Technology-Faculty of Computing and Information Technology in Rabigh King Abdulaziz University, Rabigh, Saudi Arabia; Departemen Teknik Informatika-Fakultas Ilmu Komputer, Universitas Brawijaya, Jl. Veteran, Ketawanggede, Lowokwaru, Jawa Timur, Kota Malang, 65145, Indonesia
