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Vol. 175, Issue 7, July 2014, pp. 124-131




Application of Improved Wavelet Thresholding Function in Image Denoising Processing

1 Hong Qi Zhang, 2* Hai Zhen Kang, 3 Li Hu Yi, 1 Yu Liu

1 College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot, 010018, P. R. China
2 College of Electric Power, Inner Mongolia University of Technology, Hohhot, 010051, P. R. China
3 Inner-Mongolia Electric Power Survey and Design Institute, Hohhot, 010020, P. R. China
* Tel.: +86 13948413370

* E-mail: 429535540@qq.com


Received: 12 May 2014 /Accepted: 30 June 2014 /Published: 31 July 2014

Digital Sensors and Sensor Sysstems


Abstract: Wavelet analysis is a time frequency analysis method, time-frequency localization problems are well solved, this paper analyzes the basic principles of the wavelet transform and the relationship between the signal singularity Lipschitz exponent and the local maxima of the wavelet transform coefficients mold, the principles of wavelet transform in image denoising are analyzed, the disadvantages of traditional wavelet thresholding function are studied, wavelet threshold function, the discontinuity of hard threshold and constant deviation of soft threshold are improved, image is denoised through using the improved threshold function.


Keywords: Wavelet analysis, Threshold function, Denoising, Hard threshold, Soft threshold.


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