An improved denoising method based on wavelet transform for processing bases sequence images

Ke Yan*, Jin Xing Liu, Yong Xu

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

In this article, we present an improved images denoising method for base sequence images. It is based on the multiscale analysis of the images resulting from the à trous wavelet transform decomposition. We define a new thresholding function and use it to improve the denoising performance of the isotropic undecimated wavelet transform (IUWT). The proposed method selects the best suitable wavelet function based on IUWT. The advantages of the new thresholding function are that it is more robust than previous thresholding function, and the convergence of function is more efficient. The experimental results indicate that the proposed method can obtain higher signal-to-noise ratio (SNR) and mean squared error ratio (MSE) than conventional wavelet thresholding denoising methods.

源语言英语
主期刊名Intelligent Computing Theories and Methodologies - 11th International Conference, ICIC 2015, Proceedings
编辑Vitoantonio Bevilacqua, De-Shuang Huang, Prashan Premaratne
出版商Springer Verlag
357-365
页数9
ISBN(印刷版)9783319221793
DOI
出版状态已出版 - 2015
已对外发布
活动11th International Conference on Intelligent Computing, ICIC 2015 - Fuzhou, 中国
期限: 20 8月 201523 8月 2015

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
9225
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议11th International Conference on Intelligent Computing, ICIC 2015
国家/地区中国
Fuzhou
时期20/08/1523/08/15

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