Signal Enhancement Methods Based on Wavelet Transform, Fractional Fourier Transform and Short-time Fourier Transform

Xindan Zhang; Haoyuan Zheng

doi:10.54097/eyfndn07

Authors

Xindan Zhang
Haoyuan Zheng

DOI:

https://doi.org/10.54097/eyfndn07

Keywords:

Signal enhancement, Wavelet transform, Fractional Fourier Transform (FrFT), Short-time Fourier transform (STFT).

Abstract

This review paper mainly focuses on different signal enhancement methods such as wavelet transform, fractional Fourier transform (FrFT) and short-time Fourier transform (STFT). First, this paper introduces the concept and importance of signal enhancement, as well as some current issues and challenges. Then, in recent years, the application of the three methods in wavelet transform, fractional Fourier transform and short-time Fourier transform is described. In terms of wavelet transform, this paper discusses the application of wavelet function to image enhancement and the specific steps, and analyzes its advantages and application in signal enhancement. In terms of fractional Fourier transform, this paper introduces its difference from traditional Fourier transform, and discusses its application in combination with adaptive filtering technology and the application of multi-level FrFT in the field of speech enhancement. Finally, in terms of short-time Fourier transform, this paper discusses its application in the fields of image enhancement and speech enhancement. The review paper finally discusses the characteristics, advantages and limitations of these three methods in signal enhancement, and looks forward to the future research directions. Through the research of this review paper, it can provide some reference and guidance for the research in the field of signal enhancement.

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References

Löllmann H W, Barfuss H, Deleforge A, et al. Challenges in acoustic signal enhancement for human-robot communication [C] // Speech Communication; 11. ITG Symposium. 2014: 1-4.

H. Tang, S. Lu, G. Qian, J. Ding, Y. Liu and Q. Wang, "IoT-Based Signal Enhancement and Compression Method for Efficient Motor Bearing Fault Diagnosis," in IEEE Sensors Journal, 2021, 21 (2): 1820-1828.

H. Demirel and G. Anbarjafari, "Discrete Wavelet Transform-Based Satellite Image Resolution Enhancement," in IEEE Transactions on Geoscience and Remote Sensing, 2011, 49 (6): 1997-2004.

H. Demirel and G. Anbarjafari, “Satellite image resolution enhancement using complex wavelet transform,” IEEE Geosci. Remote Sens. Lett., 2010, 7 (1): 123–126.

Wang R. Exploring Wavelet Transform-Based Image Enhancement Algorithm for Image Restoration of Long March National Cultural Park[J]. Journal of Environmental and Public Health, 2022.

Prajna, K., Mukhopadhyay, C.K. Fractional Fourier Transform Based Adaptive Filtering Techniques for Acoustic Emission Signal Enhancement. J Nondestruct Eval 39, 14 (2020).

Fan Zhenyan, Zhuang Xiaodong, Li Zhongxiao. Multistage FrFT speech enhancement based on the transform domain sparsity measure [J]. Computer Engineering and Design, 2020, 41 (09): 2574-2584.

Kulkarni D S, Deshmukh R R, Shrishrimal P P. A review of speech signal enhancement techniques[J]. International Journal of Computer Applications, 2016, 139 (14).

Z. -Q. Wang, G. Wichern, S. Watanabe and J. Le Roux, "STFT-Domain Neural Speech Enhancement with Very Low Algorithmic Latency," in IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2023, 31: 397-410.

Y. Tang, L. Jiang, Y. Hou and R. Wang, "Contactless Fingerprint Image Enhancement Algorithm Based on Hessian Matrix and STFT," 2017 2nd International Conference on Multimedia and Image Processing (ICMIP), Wuhan, China, 2017: 156-160.