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  • 标题:A Novel Extreme Learning Machine based Denoising Algorithm
  • 本地全文:下载
  • 作者:Zhiyong Fan ; Quansen Sun ; Feng Ruan
  • 期刊名称:International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 印刷版ISSN:2005-4254
  • 出版年度:2016
  • 卷号:9
  • 期号:2
  • 页码:159-166
  • DOI:10.14257/ijsip.2016.9.2.14
  • 出版社:SERSC
  • 摘要:We introduce a fast and effective algorithm extreme learning machine (ELM) and apply it to image denoising. GA-ELM algorithm we proposed uses genetic algorithm(GA) to decide weights and bias in the ELM. It has better global optimal characteristics than traditional optimal ELM algorithm. In this paper, we used GA-ELM to do image denosing researching work. Firstly, this paper uses training samples to train GA-ELM as the noise detector. Then, we utilize the well-trained GA-ELM to recognize noise pixels in target image. And at last, an adaptive weighted average algorithm is used to recover noise pixels recognized by GA-ELM. Experiment data shows that this algorithm has better performance than other denosing algorithm.
  • 关键词:image denoising; extreme learning machine; genetic algorithm; rank- ; ordered logarithmic difference
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