NDLI: Study on robust noise reduction algorithm based on wavelet transfrom

Content Provider	IEEE Xplore Digital Library
Author	Jian Wang Meng Xiangchao
Copyright Year	2011
Description	Author affiliation: Environmental and Spatial Informatics, China University of Mining and Technology, Xuzhou, China (Meng Xiangchao) \|\| Key Laboratory for Land Environment and Disaster Monitoring of SBSM, CUMT, Xuzhou 221116, China (Jian Wang)
Abstract	Based on the principle of wavelet transform, the basic assumptions of wavelet denoising is analyzed. In this paper we propose a robust wavelet transform algorithm using a α - trimmed mean filter as a “agent” component based on Donoho's soft thresholding shrinkage method. And on this basis, a detailed analysis on the structure of two-dimensional wavelet transform is made; two-dimensional robust wavelet transform algorithm is built, and applied to image noise reduction. One-dimensional signal with noise and gross error test results show that the effectiveness of robust wavelet transform. This paper also uses image analysis with salt and pepper noise, compared to traditional wavelet denoising algorithm. The results show that the algorithm can effectively remove impulse noise in the image, but it will make the image fuzzy if the gross error threshold is set to some extent inappropriate.
Starting Page	3553
Ending Page	3556
File Size	307045
Page Count	4
File Format	PDF
ISBN	9781424491728
e-ISBN	9781424491711
DOI	10.1109/RSETE.2011.5965094
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wavelet transforms Algorithm design and analysis Noise reduction Noise Filtering algorithms Robustness α trimmed filter Wavlet
Content Type	Text
Resource Type	Article

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