Transmission Map Optimization for Single Image Dehazing

MULTIMODAL IMAGE EXPLOITATION AND LEARNING 2022(2022)

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摘要
In hazy weather, images and videos captured outdoor scenes often suffer from inadequate visibility, low contrast, and color shift due to the atmospheric light scattering from the atmosphere particles. In general, the haze is not uniformly distributed. It is a high challenge in computer vision-based applications to visualize matters behind hazy scenes like haze-free images. This paper aims to: i) develop a new optimal-based transmission map for removing haze or fog from a single image and a video; and ii) demonstrate the utility and effectiveness of the developed technique. The proposed method offers a single image de-hazing algorithm based on transmission map optimization and novel enhancement techniques. Intensive computer simulation results of natural Live-Haze dataset and synthetic image datasets such as O-HAZY, dataset show that: 1. The presented approach effectively removes haze and prevents color distortion from undesirable de-hazing. 2. The resulting dehazed images illustrate realistic colors and remarkable details. 3. The proposed method achieves to restore the visibility of hazy scenes and illustrates colorful and natural appearances.
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关键词
Image Dehazing, Image Enhancement, Scene Restoration, Visibility Restoration
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