FourierMellin描述子被广泛应用于数字图像匹配中，但由于频谱混叠等噪声及误差的存在，不能保证变化后得到的相关值分布形式是一个标准的二维脉冲函数。本文在此基础上引入带核函数的加权距离公式，先用小波变换在频域中提取出稳定的特征点形成特征向量；然后利用核函数对特征向量进行修正，使之形成标准的二维脉冲函数，以便计算出正确的匹配参数，从而达到两幅图像的匹配。实验结果表明了新算法的有效性和可靠性。

The FourierMellin descriptor has been widely applied in digital image matching. However, because of the noise of spectrum aliasing and errors, the Fourier Mellin descriptor can not be sure that the form of the changed relative value distribution is the standard twodimensional pulse function. Based on the basis of introducing the distance formula with a kernel function, first using wavelet transform in the frequency domain extract stable feature points to form a  feature vector；then the kernel function is used to amend the feature vector, thus making the formation of a standard twodimensional pulse function, to correctly compute the matching parameters, so as to achieve the matching result of two images. The experimental results show that the new algorithm is efficient and reliable.