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A multifeature fusion method for the color distortion and low contrast of underwater images

机译:水下图像颜色失真和低对比度的多因素融合方法

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摘要

Light is scattered and absorbed when it is transmitted through seawater. Underwater images captured in water suffer from color attenuation, low contrast, and blurred details. To address these effects, we propose a multifeature fusion method (MFFM) to improve the color distortion and low contrast of underwater images. White balance technology is used to address the color cast of underwater images and obtain a color correction image. On this basis, the color correction image is enhanced by a guided filter to obtain a contrast-enhanced image. Four feature weights of the input images are calculated separately, and two normalized weight maps are constructed by normalization. To avoid a halo, the two normalized weight maps are multiscale fused. To improve the edge detail, the fused image is enhanced by a color adjustment technique to obtain the final enhanced image. Real underwater images are used for simulation and application testing. Compared with the current state-of-the-art methods, our method can balance the color and contrast and improve the visibility of underwater images. Extensive qualitative and quantitative experiments verify the superiority of the MFFM.
机译:当通过海水传输时,光被散射和吸收。水下图像在水中捕获的彩色衰减,低对比度和模糊细节。为了解决这些效果,我们提出了一种多因素融合方法(MFFM)来提高水下图像的颜色失真和低对比度。白平衡技术用于解决水下图像的颜色铸件并获得颜色校正图像。在此基础上,通过引导滤波器增强彩色校正图像以获得对比度增强的图像。输入图像的四个特征权重分别计算,并且通过归一化构建两个归一化权重映射。为避免光环,两个规范化的体重图是多尺度融合的。为了改善边缘详细信息,通过颜色调节技术提高融合图像以获得最终增强图像。真实的水下图像用于仿真和应用测试。与目前的最先进的方法相比,我们的方法可以平衡颜色和对比度并提高水下图像的可见性。广泛的定性和定量实验验证了MFFM的优越性。

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