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A statistical learning based image denoising approach
  • ISSN号：2095-9389
  • 期刊名称：《工程科学学报》
  • 时间：0
  • 分类：TP181[自动化与计算机技术—控制科学与工程;自动化与计算机技术—控制理论与控制工程] TP391.41[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术]
  • 作者机构：[1]Department of Computer Science and Technology, State Key Laboratory of Intelligent Technology and Systems, Tsinghua University, Beijing 100084, China
  • 相关基金：Acknowledgements This work was supported by National Basic Research Program of China （973 Program） （2012CB821206）, the National Natural Science Foundation of China （Grant No. 61473161 and 61174069）, Beijing Natural Science Foundation （4122037）, and Tsinghua University Initiative Scientific Research Program （20131089295）.
作者： Ke TU Hongbo LI Fuchun SUN[1]
关键词： 统计学习理论, 图像处理, 去噪方法, 支持向量机, 去噪性能, 图像去噪, 方差估计, 去噪算法, SVM, image denosing, multiple noises
中文摘要：

Ke Tu is now pursuing his PhD in the Department of Computer Science and Technology, Tsinghua University, China. His recent research interests include image denoising, image enhancement and data mining. E-mail： hbli@ tsinghua.edu.cnHongbo Li received the PhD from Tsinghua University, China in 2009. He is currently an assistant professor with the Department of Computer Science and Technology, Tsinghua University, China. His research interests include networked control systems and intelligent control. Fuchun Sun received the PhD in 1998 from the Department of Computer Science and Technology, Tsinghua Uni- versity, China. Currently, he is a professor in the Department of Computer Science and Technology, Tsinghua University, China. His research interests include intelligent control, neural networks, fuzzy systems, variable structure control, nonlinear systems and robotics.

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期刊信息
  • 《工程科学学报》
  • 北大核心期刊（2011版）
  • 主管单位:中华人民共和国教育部
  • 主办单位:北京科技大学
  • 主编：张欣欣
  • 地址：北京市海淀区学院路30号
  • 邮编：100083
  • 邮箱：xuebaozr@ustb.edu.cn
  • 电话：010-62332875
  • 国际标准刊号：ISSN：2095-9389
  • 国内统一刊号：ISSN：10-1297/TF
  • 邮发代号:82-303
  • 获奖情况:
  • 首届国家期刊奖,第二届全国优秀科技期刊评比一等奖,全国高等学校自然科学学报系统优秀学报评比一等奖,中国期刊方阵“双高”期刊
  • 国内外数据库收录:
  • 日本日本科学技术振兴机构数据库,中国北大核心期刊（2004版）,中国北大核心期刊（2008版）,中国北大核心期刊（2011版）,中国北大核心期刊（2014版）
  • 被引量:392