小波变换在雾霾和噪声图像处理中的应用

Zeli Wang, Xiaoting Liu, Xiaomei Zhang
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引用次数: 0

摘要

为了增强低质量图像的可视化,适应雾霾天气下公安图像检测和视觉检测的实际工作,我们整合了目前广泛应用的处理方法,采用了一种新的处理方法。该方法利用四叉树方法解决了暗通道先验大气光值的选择缺陷问题。针对小波分频重构系数之间的干扰影响,采用梯度下的自适应相关方法。对于随小波系数增大而增大的噪声,给出了一种折衷阈值的降噪方法。实验结果表明,该算法的图像层次对比度好,色彩保真度好,各项指标普遍优于其他算法。
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A Effective Method Using Wavelet Transform for Haze and Noisy Image
In order to enhance the visualization of low-quality images and adapt to the practical work of public security picture detection and visual detection in haze weather, we integrate the currently widely applicable processing methods and adopt a new processing method. This method uses the quad-tree method to solve the problem of the selection defect of the priori atmospheric light value of the dark channel. Aiming at the interference effect between the wavelet frequency division reconstruction coefficients, the adaptive correlation method under the gradient is applied. For noise that gains along with wavelet coefficients, we gives a noise reduction method by compromises the threshold. The experimental results show that the hierarchical contrast of the image is fine, the color fidelity is fine, and the indicators are generally better than other algorithms.
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