Published on: May 2026
DEHAZING AND SENSOR FUSION FOR SAFE NAVIGATION IN LOW-VISIBILITY ENVIRONMENTS
Girish Kapse Neha Sharma Nikita Deepak
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Abstract
Therefore, an algorithm-based solution integrating image de-hazing techniques and sensor fusion is presented. The Dark Channel Prior (DCP) method is used for estimating the atmo-sphere light and obtaining the true light of the scene. Moreover, the CLAHE algorithm is applied on the LAB color channel to increase the contrast without introducing more noise into the image.
The proposed solution uses an ultrasonic sensor for obstacle detection, and its data is fused with visual input. The architecture consists of an ESP32-CAM camera module for acquiring images, an Arduino UNO board for working with the ultrasonic sensor, and a Flask application as a backend, utilizing OpenCV and NumPy libraries.
Experimental results have shown improvement in image clar-ity, contrast, and increased obstacle detection efficiency.
Keywords: Image Dehazing, Sensor Fusion, Dark Channel Prior, CLAHE, Autonomous Navigation, Embedded Systems, Low-Visibility Systems
How to Cite this Paper
Kapse, G., Sharma, N., Nikita, & Deepak, (2026). Dehazing and Sensor Fusion for Safe Navigation in Low-Visibility Environments. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(05). https://doi.org/10.55041/ijcope.v2i5.694
Kapse, Girish, et al.. "Dehazing and Sensor Fusion for Safe Navigation in Low-Visibility Environments." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 05, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i5.694.
Kapse, Girish,Neha Sharma, Nikita, and Deepak. "Dehazing and Sensor Fusion for Safe Navigation in Low-Visibility Environments." International Journal of Creative and Open Research in Engineering and Management 02, no. 05 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i5.694.
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References
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- •Published on: May 23 2026
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