A fast recursive algorithm for two-dimensional thresholding

Gong Jian, Liang Liyuan, Chen Weinan
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引用次数: 15

Abstract

Two-dimensional (2D) thresholding behaves well in segmenting images of low signal-to-noise ratio. But the computational complexity of the conventional 2D entropic algorithm is bounded by O(L/sup 4/). Firstly, a fast recursive 2D entropic thresholding algorithm is proposed. By rewriting the formula for calculation of the entropy in a recurrence form, a great deal of calculation is saved. Analysis shows that the computational complexity of 2D entropic thresholding is reduced to O(L/sup 2/). The fast recursive algorithm is also used successfully in the 2D Otsu (1979) method. Experimental results show that the processing time of each image is reduced from more than 2 h to less than 10 sec. The required memory space is also greatly reduced.
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二维阈值的快速递归算法
二维阈值分割在低信噪比的图像中表现良好。但传统二维熵算法的计算复杂度以0 (L/sup 4/)为限。首先,提出了一种快速递归二维熵阈值分割算法。将熵的计算公式改写为递推式,可以节省大量的计算量。分析表明,二维熵阈值的计算复杂度降低到0 (L/sup 2/)。快速递归算法在2D Otsu(1979)方法中也得到了成功的应用。实验结果表明,每幅图像的处理时间从2小时以上减少到10秒以下,所需的存储空间也大大减少。
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