基于局部模糊熵的图像过渡区提取算法
Transition Region Extraction Algorithm Based on LocalFuzzy Entropy
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摘要: 为了提高图像过渡区提取算法的抗噪声性能,对基于局部熵的图像过渡区算法加以改进,提出了基于局 部模糊熵的图像过渡区算法.该算法充分利用局部模糊熵区分过渡区与目标区(或背景区)性质的差异,更为有 效地提取出图像中的过渡区.仿真实验结果表明,这两种算法在图像含有椒盐噪声的情况下都能有效提取过渡 区,但在图像含有高斯噪声的情况下,采用本文算法比采用基于局部熵的图像过渡区算法提取的过渡区更为 准确.Abstract: To improve the performances of transition region extraction algorithmsundernoises, a novel local fuzzy entropy-based transition region algorithm was proposed by making improvement to the existing local entropy-based transition region algorithm. The proposed algorithm makes full use of the difference between transition regions and target regions (or background regions). The performance of the proposed algorithm was compared with the local entropy algorithm underGaussian noise and salt and peppernoise. The comparison shows that the proposed algorithm provideshigheraccuracy than the local entropy-based transition region extraction algorithm does under Gaussian noise, although both behavewellunder salt and peppernoise.
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Key words:
- image segmentation /
- local fuzzy entropy /
- transition region extraction /
- algorithm
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