Noise Removal for Degraded Images Using Neural Networks

• LU Jianming

  Chiba University

• Fujimoto Minoru

  Chiba University

• YAHAGI Takashi

  Chiba University

Bibliographic Information

Other Title

• ニューラルネットワークを用いた劣化画像の雑音除去
• ニューラル ネットワーク オ モチイタ レッカ ガゾウ ノ ザツオン ジョキョ

Abstract

In signal processing applications and image processing applications, some problems are difficult to process based on the linear theory. In these problems, nonlinear processing will be more suitable for obtaining better results. On the other hand, neural networks with a nonlinear input-output relation are applied to various problems such as pattern recognition and the estimation of nonlinear systems. This paper presents a method for noise removal for degraded images using neural networks. Furthermore, in order to effectively apply neural networks to noise removal of the images with different features from the teacher images, a method is proposed for using multiple neural networks to extract the features of the images properly. Finally, the results of computer simulation are presented to illustrate the effectiveness of the proposed method.

Journal

• IEEJ Transactions on Electronics, Information and Systems

  IEEJ Transactions on Electronics, Information and Systems 122 (8), 1301-1308, 2002

  The Institute of Electrical Engineers of Japan

Keywords

• Image restoration
• neural network
• digital filter
• nonlinear filter

Details

• CRID: 1390001204609880064
• NII Article ID: 130006845152
• NII Article ID: 10011086890
• NII Article ID: 10009587496
• NII Book ID: AN10065950
• DOI: 10.1541/ieejeiss1987.122.8_1301
• ISSN: 13488155
• ISSN: 03854221
• ISSN: http://id.crossref.org/issn/03854221
• NDL BIB ID: 6243940
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I6243940
• Web Site: https://www.jstage.jst.go.jp/article/ieejeiss1987/122/8/122_8_1301/_pdf
• Data Source:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
• Abstract License Flag: Disallowed