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An efficient method for the unmanned aerial vehicle image denoising

机译:无人驾驶飞行器图像去噪的有效方法

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An efficient method for the unmanned aerial vehicle (UAV) image denoising is proposed by combining an adaptive wavelet thresholding denoising and the image enhancement method in this paper. This method is aimed at improving the effect of the wavelet thresholding denoising method and enhancing the edge of the image. An adaptive threshold value which changes with the change of the decomposition scale and the direction of the subband is selected for denoising. After wavelet denoising, the image enhancement method is used for enhancing the edge of the image. Experimental results show that, compared with the other methods, the proposed method yields bigger peak signal-to-noise ratio and superior visual image quality—measured by universal image quality index. It also retains more edges and details of the image.
机译:通过组合本文的自适应小波阈值阈值和图像增强方法,提出了一种有效的无人空中车辆(UAV)图像去噪的方法。该方法旨在改善小波阈值脱落方法的效果并增强图像边缘。选择随着分解刻度的改变和子带的方向而改变的自适应阈值进行去噪。在小波去噪之后,图像增强方法用于增强图像的边缘。实验结果表明,与其他方法相比,所提出的方法产生更大的峰值信噪比和通过通用图像质量指标测量的高级别的视觉图像。它还保留了更多的边缘和图像细节。

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