UIDF-Net: Unsupervised Image Dehazing and Fusion Utilizing GAN and Encoder–Decoder
Anxin Zhao,
Liang Li,
Shuai Liu
Abstract:Haze weather deteriorates image quality, causing images to become blurry with reduced contrast. This makes object edges and features unclear, leading to lower detection accuracy and reliability. To enhance haze removal effectiveness, we propose an image dehazing and fusion network based on the encoder–decoder paradigm (UIDF-Net). This network leverages the Image Fusion Module (MDL-IFM) to fuse the features of dehazed images, producing clearer results. Additionally, to better extract haze information, we introd… Show more
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