@inproceedings{f740ee3744254114ad95b83424a4abee,
title = "An improved denoising method based on wavelet transform for processing bases sequence images",
abstract = "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 {\`a} 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.",
keywords = "Bases sequence images, Image denoising, Isotropic undecimated wavelet transform",
author = "Ke Yan and Liu, {Jin Xing} and Yong Xu",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 11th International Conference on Intelligent Computing, ICIC 2015 ; Conference date: 20-08-2015 Through 23-08-2015",
year = "2015",
doi = "10.1007/978-3-319-22180-9_35",
language = "English",
isbn = "9783319221793",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "357--365",
editor = "Vitoantonio Bevilacqua and De-Shuang Huang and Prashan Premaratne",
booktitle = "Intelligent Computing Theories and Methodologies - 11th International Conference, ICIC 2015, Proceedings",
address = "Germany",
}