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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >Improvement of Fuzzy Image Contrast Enhancement Using Simulated Ergodic Fuzzy Markov Chains
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Improvement of Fuzzy Image Contrast Enhancement Using Simulated Ergodic Fuzzy Markov Chains

机译:模拟遍历模糊马尔可夫链对模糊图像对比度增强的改进

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This paper presents a novel fuzzy enhancement technique using simulated ergodic fuzzy Markov chains for low contrast brain magnetic resonance imaging (MRI). The fuzzy image contrast enhancement is proposed by weighted fuzzy expected value. The membership values are then modified to enhance the image using ergodic fuzzy Markov chains. The qualitative performance of the proposed method is compared to another method in which ergodic fuzzy Markov chains are not considered. The proposed method produces better quality image.
机译:本文提出了一种新的模糊增强技术,该技术使用模拟遍历模糊马尔可夫链进行低对比度脑磁共振成像(MRI)。通过加权模糊期望值提出了模糊图像对比度的增强方法。然后使用遍历模糊马尔可夫链修改成员值以增强图像。将所提方法的定性性能与不考虑遍历模糊马尔可夫链的另一种方法进行比较。所提出的方法产生更好质量的图像。

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