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A color image enhancement method based on Ensemble Empirical Mode Decomposition and Genetic Algorithm

机译:一种基于集合经验模式分解和遗传算法的彩色图像增强方法

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In this paper, we introduce a new method for enhancement of the color images. The proposed approach utilizes Ensemble Empirical Mode Decomposition (EEMD) and Genetic Algorithm (GA). The algorithm is tested on the underwater images and the underexposed scenes. For the dark images, a nonlinear transform is first performed on the original image as a preliminary illumination correction. For underwater images, the mean of each RGB channels is initially corrected based on a GA-oriented technique. After the preprocessing steps, an EEMD based method is applied on the luminance channel of the resulting image to further correct the brightness of the image. The Genetic Algorithm enables the presented method to set the required parameters automatically. The experimental results demonstrate the effectiveness of the algorithm in visual enhancement of the color images.
机译:在本文中,我们介绍了一种增强彩色图像的新方法。所提出的方法利用集合经验模式分解(EEMD)和遗传算法(GA)。该算法在水下图像和曝光场景上进行了测试。对于暗图像,首先在原始图像上执行非线性变换作为初步照明校正。对于水下图像,最初基于GA导向技术校正每个RGB信道的平均值。在预处理步骤之后,基于EEMD的方法应用于所得到图像的亮度信道,以进一步校正图像的亮度。遗传算法使呈现的方法能够自动设置所需参数。实验结果证明了算法在彩色图像的视觉增强中的有效性。

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