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Curvelet Transform-Based Denoising Method for Doppler Frequency Extraction

机译:基于曲线波变换的多普勒频率去噪方法

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摘要

A novel image denoising method based on curvelet transform is proposed in order to improve the performance of Doppler frequency extraction in low signal-noise-ratio (SNR) environment. The echo can be represented as a gray image with spectral intensity as its gray values by time-frequency transform. And the curvelet coefficients of the image are computed. Then an adaptive soft-threshold scheme based on dual-median operation is implemented in curvelet domain. After that, the image is reconstructed by inverse curvelet transform and the Doppler curve is extracted by a curve detection scheme. Experimental results show the proposed method can improve the detection of Doppler frequency in low SNR environment.
机译:为了提高低信噪比环境下多普勒频率提取的性能,提出了一种基于曲线波变换的图像去噪方法。通过时频变换,回波可以表示为频谱强度为灰度值的灰度图像。并计算出图像的曲线波系数。然后在curvelet域中实现了基于双中值运算的自适应软阈值方案。之后,通过逆曲波变换重建图像,并通过曲线检测方案提取多普勒曲线。实验结果表明,该方法可以改善低信噪比环境下对多普勒频率的检测。

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