• DocumentCode
    3762098
  • Title

    Noisy image restoration based on optimized cellular neural network

  • Author

    Nima Aberomand;Seyed Mahdi Jameii

  • Author_Institution
    Department of computer Engineering, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
  • fYear
    2015
  • Firstpage
    1194
  • Lastpage
    1197
  • Abstract
    Sending multimedia file in computer networks from the source to destination can cause noisy. Some images have default noises. Other types of images in processing can be noisy due to high level process in weak systems. Creating a system for image retrieval is an important part of image processing. This article focused on noisy image restoration based on cellular neural network. Noises inside the pixel with different sizes are restored with different levels of surrounding information. Images with 50% of noise cannot be recovered correctly, but optimized cellular neural network can recover whole part of images with less noises. The main purposes of using cellular neural network are less time with more noise removal. Two evaluation methods like MSE and PSNR are used to compare with recent methods.
  • Keywords
    "Decision support systems","Image restoration","Cellular neural networks"
  • Publisher
    ieee
  • Conference_Titel
    Knowledge-Based Engineering and Innovation (KBEI), 2015 2nd International Conference on
  • Type

    conf

  • DOI
    10.1109/KBEI.2015.7436218
  • Filename
    7436218