首页    期刊浏览 2024年12月05日 星期四
登录注册

文章基本信息

  • 标题:Improved approximated median filter algorithm for real-time computer vision applications
  • 本地全文:下载
  • 作者:Obed Appiah ; Michael Asante ; James Benjamin Hayfron-Acquah
  • 期刊名称:Journal of King Saud University @?C Computer and Information Sciences
  • 印刷版ISSN:1319-1578
  • 出版年度:2022
  • 卷号:34
  • 期号:3
  • 页码:782-792
  • 语种:English
  • 出版社:Elsevier
  • 摘要:Median filter is one of the predominant filters that are used to suppress impulse noise. Its simplicity and ability to maintain edges has led to an extensive application in the domain of image processing and computer vision. However, challenges such as moderate to high running time of the standard median filter algorithm and relatively poorer performance when the image is highly corrupted with impulse noise, have led to the design of several variations of the algorithm. One set of variation of the algorithm concentrates on generating quality outputs, while the other set focuses on reducing running time. Among the set targeting the reduction of the running time of the median filter is the DP approximated median filter. However, DP performs poorly when images are corrupted with moderate to high levels of noise. This paper therefore proposes an Improved Approximation Median Filtering Algorithms (IAMFA-I & IAMFA-II) based on DP to generate a better output. The introduction of Mid-Value-Decision-Median in DP reduces the chances of selecting corrupted pixel for denoised image. Experimental results indicate that the IAMFA-II has better running time and equivalent output compared with DP, while IAMFA-I generates better output and has equivalent running time when compared with DP.
国家哲学社会科学文献中心版权所有