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An Adaptive Image Enhancement Method Based on Contourlet Transform and Improved Ant Colony Algorithm

机译:基于Contourlet变换和改进蚁群算法的自适应图像增强方法

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To overcome the problems of losing detail geometric information of images and tending to amplify noise, which exist in traditional image enhancement methods, an adaptive image enhancement method based on Contourlet transform and improved ant colony algorithm is proposed. Firstly, we obtain the coefficients in different scales and different directions by image decomposition using the Contourlet transform. Then, we adopt an adaptive enhancement function with the ability of both feature enhancement and noise reduction to modify the Contourlet coefficients nonlinearly, and use an improved ant colony algorithm to adaptively adjust the parameters of the enhancement function. To find the optimal parameters, a novel evaluation criterion for image enhancement is introduced. Finally, we obtain the enhanced image by Contourlet inverse transform. The experimental results show that our method obtains significant performance in feature enhancement with low contrast and noise reduction over the wavelet-based and Contourlet-based non-adaptive image enhancement methods.
机译:针对传统图像增强方法存在的图像细节几何信息丢失,噪声放大的趋势,提出了一种基于Contourlet变换和改进蚁群算法的自适应图像增强方法。首先,我们利用Contourlet变换通过图像分解获得了不同比例和不同方向的系数。然后,我们采用具有特征增强和降噪功能的自适应增强函数来非线性地修改Contourlet系数,并使用改进的蚁群算法来自适应地调整增强函数的参数。为了找到最佳参数,引入了一种新的图像增强评估标准。最后,我们通过Contourlet逆变换获得了增强图像。实验结果表明,与基于小波和基于Contourlet的非自适应图像增强方法相比,我们的方法在低对比度和低噪点的特征增强方面获得了显着的性能。

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