基于非冗余平移不变小波变换的医学图像配准

配准是图像处理中一个非常重要的过程,但其运算量通常非常大。离散小波变换(discrete wavelet transform,DWT)已成为减小运算量的有效工具,然而,它对平移的敏感意味着原图像特征的微小位移在其小波分解子图中可能产生不可预料的变化。本文根据分析认为平移敏感性是由DWT中降采样过程引入的混叠造成的,并以此提出了设计小波滤波器的新方法。该方法通过减小混叠影响,从而减小了DWT的平移敏感性。设计结果表明此方法使DWT的平移敏感性得到了有效抑制,同时保持了非冗余性。最后,两个医学图像的配准过程表明了该小波的有效性和设计方法的合理性。

Medical Image Registration Using the Nearly Shift-Insensitive and nonredundancy Discrete Wavelet Transform

Discrete wavelet transform （DWT） has become an attractive tool of image registration, however,it is shift-sensitive. Some modified schemes of DWT, such as DTCWT （dual-tree complex wavelet transform） ,always lead to high computational complexity in registration process because of redundancy. In this paper,it showed that the shift-sensitivity was caused by the downsampling operation in the analysis process, which could be expressed by the aliasing terms in the frequency-domain. A new scheme for the design of wavelets was proposed to approximately eliminate the effect of downsampling while remains the wavelet representation nonredundancy. The design example illustrated the shift sensitivity of wavelet representations was reduced efficiently without any redundancy. The registration results of two medical images further proved the validity of design scheme and effectiveness of the proposed wavelet.