基于局部模糊熵的图像过渡区提取算法

Transition Region Extraction Algorithm Based on Local Fuzzy Entropy

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.

To improve the performances of transition region extraction algorithms under noises, 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 under Gaussian noise and salt and pepper noise. The comparison shows that the proposed algorithm provides higher accuracy than the local entropy-based transition region extraction algorithm does under Gaussian noise, although both behave well under salt and pepper noise.