基于小波自适应阈值方法的探地雷达去噪.

Ground-penetrating radar will be disturbed by various noise signals in the actual use process, and to solve this problem, a ground-penetrating radar denoising was proposed based on wavelet adaptive thresholding method. Conventional wavelet thresholding algorithms for ground-penetrating radar B-scan images may cause image distortion due to the difference in wavelet coefficients before and after processing. In order to make the target signal clearer and eliminate interference such as noise, wavelet thresholds were improved by the way of selecting wavelet thresholds and the threshold function, and the thresholds were identified with the length of subbands of different layers of wavelet transform to achieve adaptive and accurate quantization of thresholds. The experimental results show that the method is applicable to ground-penetrating radar signal processing and improves the good continuity and stability of the threshold function compared with the ordinary wavelet thresholding algorithm, further improves the direct wave removal and noise reduction effects, and better preserves the details of the target image. Comparing the results with other methods shows that the algorithm proposed in this paper improves the peak signal-to-noise ratio and reduces the image entropy. The research results show that the method has a certain application value in the practical use case of ground-penetrating radar. [ABSTRACT FROM AUTHOR]