Underwater image enhancement based on weighted guided filter image fusion

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Dan Xiang, Huihua Wang, Zebin Zhou, Hao Zhao, Pan Gao, Jinwen Zhang, Chun Shan
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引用次数: 0

Abstract

An underwater image enhancement technique based on weighted guided filter image fusion is proposed to address challenges, including optical absorption and scattering, color distortion, and uneven illumination. The method consists of three stages: color correction, local contrast enhancement, and fusion algorithm methods. In terms of color correction, basic correction is achieved through channel compensation and remapping, with saturation adjusted based on histogram distribution to enhance visual richness. For local contrast enhancement, the approach involves box filtering and a variational model to improve image saturation. Finally, the method utilizes weighted guided filter image fusion to achieve high visual quality underwater images. Additionally, our method outperforms eight state-of-the-art algorithms in no-reference metrics, demonstrating its effectiveness and innovation. We also conducted application tests and time comparisons to further validate the practicality of our approach.

Abstract Image

基于加权导向滤波图像融合的水下图像增强技术
提出了一种基于加权导向滤波图像融合的水下图像增强技术,以应对包括光学吸收和散射、色彩失真和光照不均等挑战。该方法包括三个阶段:色彩校正、局部对比度增强和融合算法方法。在色彩校正方面,通过通道补偿和重映射实现基本校正,并根据直方图分布调整饱和度,以增强视觉丰富度。在局部对比度增强方面,该方法采用盒式滤波和变异模型来提高图像饱和度。最后,该方法利用加权引导滤波图像融合技术实现高视觉质量的水下图像。此外,我们的方法在无参考指标方面优于八种最先进的算法,证明了其有效性和创新性。我们还进行了应用测试和时间比较,以进一步验证我们方法的实用性。
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来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
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