摘要：

运用传统三维最大类间方差(Otsu)法进行森林冠层图像分割时,存在抗噪声能力差、计算复杂度高等问题。为此,基于三维Otsu法,提出一种改进的森林冠层图像分割方法。通过三维直方图重建实现去噪并保留边缘信息。将重建后的三维直方图经过降维处理分解为3个一维直方图,以降低计算复杂度,减少运行时间和存储空间。实验结果表明,相对传统三维Otsu法,该方法能够有效分割森林冠层图像,且具有更好的分割鲁棒性、准确性与实时性。

关键词: 森林冠层图像, 图像阈值分割, 三维最大类间方差法, 直方图重建, 降维

Abstract:

When using traditional three-dimensional(3D) Otsu method to segment forest canopy image,there are some problems,such as poor anti-noise ability and high computational complexity.To slove this problem,an improved forest canopy image segmentation method is proposed based on the 3D Otsu method.The 3D histogram reconstruction is used to denoise and preserve the edge information.The reconstructed 3D histogram is decomposed into three one-dimensional histograms by dimensionality reduction to reduce the computational complexity,running time and storage space.Experimental results show that compared with the traditional 3D Otsu method,this method can effectively segment forest canopy image,and has better robustness,accuracy and real-time performance.

Key words: forest canopy image, image threshold segmentation, three-dimensional(3D) Otsu method, histogram reconstruction, dimensionality reduction

中图分类号: 

• S718.42