Skip to main navigation Skip to search Skip to main content

Adaptive image enhancement method based on neural networks

  • Fuqiang Zhou*
  • , Ying Xiong
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, an adaptive image enhancement method based on neural networks is proposed. The low frequency components of the image can be obtained by average filter and the high frequency components of the image are obtained by subtracting the low frequency from the original image. The enhanced image is obtained by adding the original image to the high frequency components multiplied by the scale factor. The masking size of the average filter and the scale factor are given by the constructed neural net in terms of the mean and standard deviation of the image. Real experiments has been to test the proposed method and very good result has been obtained.

Original languageEnglish
Title of host publicationSeventh International Symposium on Instrumentation and Control Technology
Subtitle of host publicationOptoelectronic Technology and Instruments, Control Theory and Automation, and Space Exploration
DOIs
StatePublished - 2008
Event7th International Symposium on Instrumentation and Control Technology: Optoelectronic Technology and Instruments, Control Theory and Automation, and Space Exploration - Beijing, China
Duration: 10 Oct 200813 Oct 2008

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume7129
ISSN (Print)0277-786X

Conference

Conference7th International Symposium on Instrumentation and Control Technology: Optoelectronic Technology and Instruments, Control Theory and Automation, and Space Exploration
Country/TerritoryChina
CityBeijing
Period10/10/0813/10/08

Keywords

  • Adaptive
  • Image enhancement
  • Neural net

Fingerprint

Dive into the research topics of 'Adaptive image enhancement method based on neural networks'. Together they form a unique fingerprint.

Cite this