結(jié)合脈沖耦合神經(jīng)網(wǎng)絡與模糊算法進行四值圖像去噪
Noise-Reducing of Fourlevel Image Using PCNN and Fuzzy Algorithm
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摘要: 該文研究了如何將模糊算法用于脈沖耦合神經(jīng)網(wǎng)絡(Pulse Coupled Neural Network,PCNN),進行四值圖像去噪,提出了基于模糊PCNN的圖像去噪算法.計算機仿真結(jié)果表明,將模糊算法與PCNN相結(jié)合,可有效地去除被噪聲污染的四值圖像的噪聲,且恢復圖像的視覺效果明顯地好于用另兩種常用的圖像去噪方法(中值濾波和均值濾波)得到的結(jié)果.在醫(yī)用圖像和軍事圖像處理方面,四值圖像的去噪恢復是非常有價值的,故本文對于PCNN的理論研究和實際應用均有重要的意義。
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關鍵詞:
- 模糊PCNN; 圖像去噪
Abstract: This paper describes how to combine PCNN(Pulse Coupled Neural Network) with fuzzy algorithm to reduce the noise of four-level images. Meanwhile, the image noise-reduciug algorithm based on the fuzzy PCNN is brought forward. The results of computer simulations show that noisy four-level images can be restored efficiently by using fuzzy PCNN and visual effects of restoration images by using fuzzy PCNN are much better than those by using two usual image noising-reducing methods, the median filter and the mean filter. Noise-reducing of the four-level images plays an important role in the medical image processing and the military image processing, Therefore, this paper contributes to both the theoretical researches on PCNN and the applications of PCNN. -
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