基于径向基函数的图像配准

2010 Second International Conference on Machine Learning and Computing Pub Date : 2010-02-09 DOI:10.1109/ICMLC.2010.66

R. Rajeswari, A. Irudhayaraj

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引用次数: 1

摘要

采用径向基函数(RBF)对源图像与目标图像进行配准。RBF网络的训练是通过输入源图像和目标图像的特征点的X、Y坐标来完成的。输出层中的目标输出作为源图像与目标图像对齐所需的水平位移、垂直位移、旋转角度的量和方向。这种方法可以减少校准误差。

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Image Registration Using Radial Basis Function

Radial basis function(RBF) is used to register source image with target image. Training the RBF network is done with inputs as X,Y co-ordinates of the characteristic points from source and target images. The target output in the output layer is taken as the amount and direction of horizontal shift, vertical shift, angle of rotation required to align source image with target image. This approach results in less alignment error.

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2010 Second International Conference on Machine Learning and Computing

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