计算机工程 ›› 2008, Vol. 34 ›› Issue (1): 198-200,.doi: 10.3969/j.issn.1000-3428.2008.01.068

• 人工智能及识别技术 • 上一篇    下一篇

噪声对基于不同梯度算子的ICG算法的影响

张 培,吴亚锋   

  1. (西北工业大学数据处理中心,西安 710072)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2008-01-05 发布日期:2008-01-05

Influence of Noise on ICG Algorithm Based on Different Gradient Operators

ZHANG Pei, WU Ya-feng   

  1. (Data Processing Center, Northwestern Polytechnical University, Xi’an 710072)
  • Received:1900-01-01 Revised:1900-01-01 Online:2008-01-05 Published:2008-01-05

摘要: 反向合成梯度算法是一种基于局部指向性的反向合成图像对齐算法,能有效克服光照变化对匹配结果准确性的影响。局部指向性的计算在本质上是梯度的计算,可以用不同的梯度算子求解。该文采用4种梯度算子计算局部指向性,通过给输入图像和模板图像中加入噪声模拟实际图像,研究了噪声对基于4种梯度算子的反向合成梯度算法的影响。

关键词: 反向合成, 图像对齐, 局部指向性, 反向合成梯度算法, 梯度算子

Abstract: The Inverse Compositional Gradient(ICG) algorithm is a novel Inverse Compositional Image Alignment (ICIA) algorithm, which is based on the local orientation. Compared with the ICIA algorithm, the ICG algorithm gives more accurate and reliable matching results under different lighting conditions. The evaluation of the local orientation and gradient is essentially equivalent. Hence four different gradient operators are used to compute the local orientation. White Gaussian noise is added to the input or the template images to imitate those in the real world. Performances of the ICG algorithm using the above four gradient operators under different noise, are compared.

Key words: inverse compositional, image alignment, local orientation, inverse compositional gradient algorithm, gradient operators

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