Improved segmentation method of 2-D Otsu infrared image
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摘要: 为了在2维直方图上用Otsu方法更好地分割红外图像、提高抗噪能力，提出了一种改进的方法。首先分析在2维灰度-邻域均值直方图上的分割存在不准确性，采用2维灰度-梯度直方图，且改进对邻域均值的求取算法；然后对Otsu法的阈值函数进行研究，引入类内的分离信息改进阈值函数，并简化该阈值函数以降低运算复杂度，通过实验给出了相应的实验对比。结果表明，改进的方法能更好地分割目标，运行时间较少、抗噪性更强。Abstract: In order to gain better segmentation result of infrared images, and improve the ability to resist noise, an improved 2-D Otsu method was proposed. The inaccurate segmentation in the 2-D gray-neighborhood average histogram was analyzed, and 2-D gray-gradient histogram was adopted. A new algorithm to gain neighborhood average value was put forward. Information of within-cluster was added to amend threshold function, which was further simplified to reduce the calculation complex. Experiments show that the improved method can segment the target better, gain better noise resistance and cost less time.
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Keywords:
- image processing /
- Otsu method /
- neighborhood average value /
- threshold function
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