基于最小相对熵与水平集的图像分割与校正

doi:10.16182/j.issn1004731x.joss.201711019

系统仿真学报 ›› 2017, Vol. 29 ›› Issue (11): 2731-2741.doi: 10.16182/j.issn1004731x.joss.201711019

基于最小相对熵与水平集的图像分割与校正

潘修强¹, 山金孝², 杨彩凤³

1.浙江工贸职业技术学院,浙江温州 325000;
2.招商银行信息技术部,重庆 404100;
3.重庆市沙坪坝区人民医院,重庆 404100

收稿日期:2016-05-30 发布日期:2020-06-05
作者简介:潘修强(1978-),男,浙江永嘉,硕士,副教授,研究方向为图像处理、最优化控制;山金孝(1987-),男,云南文山,硕士,研究方向为模式识别与图像分割。
基金资助:
浙江省科技计划项目(2016C32103),浙江省专业领军项目(lj2013146)

Image Segmentation and Offset Correction Based on Minimal Relative Entropy Theoryand Level Set Method

Pan Xiuqiang¹, Shan Jinxiao², Yang Caifeng³

1. Zhejiang Industry & Trade Vocational College, Wenzhou325000, China;;
2. Information Technology Department of China Merchants Bank, Chongqing404100, China;
3. People's Hospital of Chongqing Shapingba District, Chongqing404100, China

Received:2016-05-30 Published:2020-06-05

摘要/Abstract

摘要： 根据最小相对熵理论,从统计建模的角度出发建立起能量泛函,然后与水平集方法集合得到一种新的变分水平集方法,将该方法运用到了强度异质图像中进行目标分割与偏差校正。通过水平集函数的演化,将目标分割与偏差校正进行了统一,得到了具有内在平滑性的偏差估计函数。实验表明,经过校正之后,组织之间的重叠区域明显降低,分割结果更为准确。此外,模型对轮廓初始化并不敏感,需要的迭代次数和时间较少,适合于各种数据量较大的自动化应用场合。

关键词: 相对熵, 图像分割, 偏差校正, 水平集方法

Abstract: The new variational level set method is achieved with the combination of the traditional level set method and the energy function which is established by means of statistical model according to the minimal relative entropy.The new method isappliedto object segmentation and offset correction in intensity heterogeneous image.Object segmentation and offset correction are unified according to the evolution of the level set function, anda deviation estimation function with intrinsic smooth feature is obtained.The results prove that the overlapping areas between different tissues are significantly decreased and more accurate results are achieved. In addition, this model is not sensitive to contour initialization, and can achieve the desired effect with fewer iterations and shorter calculation time, which issuitable for the process of various automation applications in practice with large amount of data.

Key words: relative entropy, image segmentation, offset correction, level set method

中图分类号:

TP391.41

潘修强, 山金孝, 杨彩凤. 基于最小相对熵与水平集的图像分割与校正[J]. 系统仿真学报, 2017, 29(11): 2731-2741.

Pan Xiuqiang, Shan Jinxiao, Yang Caifeng. Image Segmentation and Offset Correction Based on Minimal Relative Entropy Theoryand Level Set Method[J]. Journal of System Simulation, 2017, 29(11): 2731-2741.

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基于最小相对熵与水平集的图像分割与校正

Image Segmentation and Offset Correction Based on Minimal Relative Entropy Theoryand Level Set Method

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