Xinli Cao, Junqiao Xiong, Yuxin Shang, Changrui Liu, Lianying Zou
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An Improved Algorithm for Defogging Based on Fused Underwater Images
This paper describes an improved algorithm for de-fogging based on fusion underwater images. Based on the fusion principle, our algorithm only needs to obtain its input map and weight map through the original degraded image. To overcome the limitations of underwater media, we define two inputs, representing color correction and contrast enhancement of the original underwater image, and four weights, which aim to enhance distant objects degraded by medium scattering and absorption visibility. Our method is a single-image method and does not require specialized hardware or knowledge about underwater conditions or scene structure. Our fusion framework also supports temporal correlation between adjacent images by applying an efficient edge denoising strategy. The enhanced image features reduced noise levels, improved exposure in dark areas, and increased overall contrast, while significantly enhancing the finest details and edges.