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Curvelet Transform Based Infrared Image Denoising Scheme

机译:基于Curvelet变换的红外图像去噪方案。

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The wavelet transform has the defect in the analyzing the edge characteristic of curves or straight lines in two-dimensional image, it doesn't has better approaching accuracy and spare ability of expression. This paper presents a improved threshold image denoising method based on the Curvelet transform, which combines the soft and the hard threshold together, and forms a new threshold function. Results of Experiment to the infrared image and the visible light image show that the method can remove noise and remain edge with good infrared usual effect comparing with the soft and hard threshold denoising algorithm and orthogonal wavelet transform denoising algorithm,and the PSNR is also enhanced extent.
机译:小波变换在分析二维图像中曲线或直线的边缘特征时存在缺陷,没有更好的逼近度和表达能力。提出了一种基于Curvelet变换的改进阈值图像去噪方法,将软阈值和硬阈值结合在一起,形成了新的阈值函数。对红外图像和可见光图像的实验结果表明,与软,硬阈值去噪算法和正交小波变换去噪算法相比,该方法能够去除噪声并保留边缘,具有良好的红外常规效果,并且PSNR也提高了一定程度。 。

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