Abstract
Aiming at the problem of noise in the traffic monitoring, especially at night, an image denoising algorithm is proposed. Application of correlation denoising algorithm based on wavelet transform in traffic monitoring. Firstly, Haar wavelet is used as the transform matrix, then image data are denoised. And The similarity of the image is evaluated by the peak signal to noise ratio. Finally, the obtained data is compared with the algorithm of existing adaptive threshold. It is found that the improved algorithm of correlation denoising achieved the expected effect and can denoise the monitoring image of nighttime very well.
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Zhang L, Bao P (2003) Denoising by spatial correlation thresholding. IEEE Trans Circuits Syst Video Technol 13(6):535–538
Portilla J, Simoncelli EP (2000) Image denoising via adjustment of wavelet coefficient magnitude correlation. In: Proceedings of international conference on image processing. IEEE, vol 3, pp 277–280
Zhan DQ, Sun SQ, Zhou Q et al (2004) Wavelet denoising and optimization of two-dimensional correlation IR spectroscopy. Spectrosc Spectral Anal 24(12):1549
Portilla J, Strela V, Wainwright MJ et al (2003) Image denoising using scale mixtures of Gaussians in the wavelet domain. IEEE Trans Image Process Publ IEEE Sig Process Soc 12(11):1338
Sardy S (2000) Minimax threshold for denoising complex signals with waveshrink. IEEE Trans Sig Process 48(4):1023–1028
Buades T, Lou Y, Morel JM et al (2015) A note on multi-image denoising. In: International workshop on local and non-local approximation in image processing. IEEE, pp 1–15
Acknowledgements
Project fund:
1. Natural Science Research Project of Anhui Province. Item Number: KJ2017A522;
2. Anhui Sanlian university research fund. Item Number: Yjt16002;
3. Anhui Sanlian university research fund. Item Number: kjzd2016002;
4. Anhui Sanlian university research fund. Item Number: PTZD2017001;
5. Anhui Sanlian university research fund. Item Number: 14zlgc045;
6. Anhui Sanlian university research fund. Item Number: kjyb2016002.
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Yang, L., Xue, F., Wang, H.h., Cheng, H.w. (2018). Research on Algorithm of Correlation Denoising Based on Wavelet Transform. In: Jia, L., Qin, Y., Suo, J., Feng, J., Diao, L., An, M. (eds) Proceedings of the 3rd International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2017. EITRT 2017. Lecture Notes in Electrical Engineering, vol 482. Springer, Singapore. https://doi.org/10.1007/978-981-10-7986-3_98
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DOI: https://doi.org/10.1007/978-981-10-7986-3_98
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