Power Law-Based Night-Time Image Dehazing Fused with Luminance Mapping for Enhanced Visibility

Dehazing at night time is an important subject to study in computer vision and image processing. The present research focused on significant challenges such ambient light estimate, guided filtering, reflection mapping, and image enhancing techniques in order to properly restore clarity and quality of photos that are taken in low-light and foggy conditions. The paper illustrates how to enhance the detail preservation, and overall visual appeal with the interaction of atmospheric light, reflection mapping, guided filtering, luminance mapping. Furthermore, the addition of the gamma parameter to tone mapping enhance the user’s artistic and interpretive abilities with previously unheard-of control over brightness and contrast adjustments. In order to ensure visually balanced and artistically pleasing outcomes in the dehazing algorithm, the luminance mapped section modifies the luminance of the dehazed image based on tone-mapped luminance values. By bringing colour channels’ brightness levels into harmony, it improves the overall quality of the dehazed output. The paper successfully manage the complexity of poorly light and foggy settings with the designed framework, which improved transportation, outdoor photography, surveillance, and other sectors. This study shows how interdisciplinary collaboration and technological development may alter the way we see our surroundings at night.