| 书目名称 | Noise Reduction by Wavelet Thresholding |
| 编辑 | Maarten Jansen |
| 视频video | |
| 丛书名称 | Lecture Notes in Statistics |
| 图书封面 |  |
| 描述 | Wavelet methods have become a widely spread tool in signal and image process ing tasks. This book deals with statistical applications, especially wavelet based smoothing. The methods described in this text are examples of non-linear and non parametric curve fitting. The book aims to contribute to the field both among statis ticians and in the application oriented world (including but not limited to signals and images). Although it also contains extensive analyses of some existing methods, it has no intention whatsoever to be a complete overview of the field: the text would show too much bias towards my own algorithms. I rather present new material and own insights in the questions involved with wavelet based noise reduction. On the other hand, the presented material does cover a whole range of methodologies, and in that sense, the book may serve as an introduction into the domain of wavelet smoothing. Throughout the text, three main properties show up ever again: sparsity, locality and multiresolution. Nearly all wavelet based methods exploit at least one of these properties in some or the other way. These notes present research results of the Belgian Programme on Interuniver s |
| 出版日期 | Book 2001 |
| 关键词 | MATLAB; Markov; Regression; Signal; Wavelet; algorithm; image processing |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4613-0145-5 |
| isbn_softcover | 978-0-387-95244-4 |
| isbn_ebook | 978-1-4613-0145-5Series ISSN 0930-0325 Series E-ISSN 2197-7186 |
| issn_series | 0930-0325 |
| copyright | Springer Science+Business Media New York 2001 |
发表于 2025-3-21 19:19:24
