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Underwater image enhancement using blending of CLAHE and percentile methodologies

机译:使用CLAHE和百分位方法相结合的水下图像增强

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In this paper, a method has been proposed for enhancement of underwater images commonly suffering from low contrast and degraded shading quality. The entirety of the image is changed when we move to capture of images, from air to the water. During capturing some absorption, reflection and scattering effects are induced in the form of contrast, quality and noise as the images look hazy or blurred. This makes one shading to overwhelm the image. For use of underwater resources and overcome these factors the enhancement of the images is required. So, in this paper, we proposed a strategy for underwater image enhancement using Contrast-Limited Adaptive Histogram Equalization (CLAHE) and Percentile methodologies. Finally, these two methodologies are blended for improving the outcomes. Two parameters, namely, Root Mean Squared Error (RMSE) and entropy have been considered for comparing the experimental results of the proposed methodology with the state-of-the-art works. It has been noticed that the proposed system performs better than already existing techniques for underwater image enhancement.
机译:在本文中,已经提出了一种用于增强水下图像的方法,该水下图像通常遭受低对比度和阴影质量下降的困扰。当我们从空中到水中捕获图像时,整个图像都会改变。在捕获某些吸收时,由于图像看起来模糊或模糊,会以对比度,质量和噪声的形式引发反射和散射效果。这使阴影不堪重负。为了使用水下资源并克服这些因素,需要增强图像。因此,在本文中,我们提出了一种使用对比度有限的自适应直方图均衡化(CLAHE)和百分位数方法的水下图像增强策略。最后,将这两种方法进行混合以改善结果。已经考虑了两个参数,即均方根误差(RMSE)和熵,以将所提出的方法的实验结果与最新技术进行比较。已经注意到,提出的系统比用于水下图像增强的现有技术表现更好。

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