基于SIRA的红外和可见光图像未爆弹目标配准方法

A Stable Interactive Registration Algorithm-based Infrared and Visible Light Image Registration Method for Unexploded Ordnance Targets

  • 摘要: 针对红外和可见光成像技术在未爆弹(Unexploded Ordnance,UXO)探测中图像背景复杂、互信息度低、有效特征点少导致配准困难的问题,在Imregtform算法基础上提出了一种稳定的交互式配准算法(Stable Interactive Registration Algorithm, SIRA)。首先结合Cpselect算法实现图像关键节点的精确配准,通过算术平均聚合作为初始矩阵。同时融合对比度受限自适应直方图均衡化算法(Contrast Limited Adaptive Histogram Equalization, CLAHE)对图像进行自适应分割并均衡化,限制对比度避免过度增强,结合双线性插值保证区域之间的平滑连续,以保证配准迭代过程中的稳定性。引入矩阵弗罗贝尼乌斯接近度(Matrix Frobenius Proximity, MFP)作为配准评估指标,缓解传统评估指标的波动性。实验结果表明,SIRA与Imregtform算法相比,配准效率提升4.72倍,MFP提升15.47倍,该算法对UXO图像配准具有更高的精度与稳定性。

     

    Abstract: A stable interactive registration algorithm (SIRA) based on the Imregtform algorithm is proposed to address issues such as complex image backgrounds, low mutual information, and few effective feature points, leading to registration difficulties in the detection of unexploded ordnance (UXO) using infrared and visible-light imaging techniques. First, the Cpselect algorithm is incorporated to realize the accurate alignment of the key nodes of an image, which are aggregated by arithmetic averaging as the initial matrix. The contrast-limited adaptive histogram equalization (CLAHE) algorithm is incorporated to adaptively segment and equalize the image and avoid contrast over-enhancement, combined with bilinear interpolation to ensure smooth continuity between the regions and a stable iterative alignment process. Matrix Frobenius proximity (MFP) was introduced as an alignment evaluation index to alleviate the volatility of traditional evaluation indices. Experimental results show that SIRA enhanced the alignment efficiency by approximately 4.72× and MFP by 15.47× compared to the Imregtform algorithm. The algorithm exhibited high accuracy and stability for UXO image alignment.

     

/

返回文章
返回