Weighted fuzzy mean filters for heavy-tailed noise removal

Chang Shing Lee, Yau Hwang Kuo, Pao Ta Yu

研究成果: Paper

16 引文 斯高帕斯(Scopus)

摘要

A new fuzzy filter, called Weighted Fuzzy Mean (WFM) filter is proposed and analyzed in this paper. The WFM filter is powerful for removing heavy additive impulse noises from images. By the filtering of each WFM filter, the filtered output signal is the mean value of the corrupted signals in a sample matrix, and these signals are weighted respectively by a membership grade of an associated fuzzy number stored in a knowledge base. The knowledge base contains a set of fuzzy numbers decided by experts or derived from the histogram of referred image. When the probability of occurrence of mixed impulse noises is over 0.3, the WFM filter can recover the noise-corrupted image quite well in contrast with the conventional filters, for examples, the median filters, nonlinear mean filters, RCRS, WOS, CWM, and stack filters, based on the Mean Absolute Error (MAE) and Mean Square Error (MSE) criteria. Besides, on the subjective evaluation of filtered images, the WFM filter results in a higher quality of global restoration.

原文English
頁面601-606
頁數6
出版狀態Published - 1995 十二月 1
事件Proceedings of the 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society, (ISUMA - NAFIPS'95) - College Park, MD, USA
持續時間: 1995 九月 171995 九月 20

Other

OtherProceedings of the 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society, (ISUMA - NAFIPS'95)
城市College Park, MD, USA
期間95-09-1795-09-20

    指紋

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mathematics(all)

引用此

Lee, C. S., Kuo, Y. H., & Yu, P. T. (1995). Weighted fuzzy mean filters for heavy-tailed noise removal. 601-606. 論文發表於 Proceedings of the 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society, (ISUMA - NAFIPS'95), College Park, MD, USA, .