A Novel Wavelet Denoising Method for IR Spectrum Based on Bat Algorithm
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State Key Laboratory For Electronic Measurement Technology, North University of China,Engineering Technology Research Center of Shanxi Province for Opto-Electronic Information and Instrument,Engineering Technology Research Center of Shanxi Province for Opto-Electronic Information and Instrument

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TN219

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    Abstract:

    To solve the problems present in traditional wavelet denoising methods, such as unexpected oscillation occurring and loss of characteristic information, a novel and effective wavelet denoising method for IR spectrum based on bat algorithm (BA) is proposed. In the method, both threshold and estimation factor are optimized by BA innovatively. Its basic idea is that firstly a certain size of individuals are generated in the solution space randomly and then the velocity and location of each bat are updated according to its distance from the best bat individual. Meanwhile, by using the random walking characteristics of Levy flight search strategy, the search for the whole solution space can be implemented and falling into the local minimum can be avoided. The experimental result of CO gas IR spectrum denoising shows that after the threshold and estimating factor in each layer of wavelet decomposition are optimized by using the proposed wavelet denoising method, the signal-to-noise ratio (SNR) is up to 84.184 and the root square error (RMSE) is 0.0006. Because the characteristic information in the spectral signal is reserved and the unwanted noise information is removed more accurately, the method can be used to improve the accuracy of subsequent qualitative and quantitative analysis.

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chenyuanyuan, wangzhibin, wangzhaoba. A Novel Wavelet Denoising Method for IR Spectrum Based on Bat Algorithm[J]. Infrared,2014,35(6):30~35

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