说明：  针对CT 医学图像和MR I 医学图像成像特点, 提出了基于快速整数提升小波变换的融合方法。在CT 和 MR I 两幅医学图像配准的前提下, 利用提升小波变换把图像分解成低频和高频子图像, 对于小波变换后的高频 子图像, 选择区域标准差大的作为融合后的子图像 对于低频子图像, 采用加权融合, 最后进行小波逆变换, 得到 融合后的图像, 并对融合后图像用信息熵、平均梯度、相关系数的指标进行评价。实验结果表明, 基于快速整数提 升小波变换融合中, 小波高低频系数采用不同的规则能够取得更好的融合效果, 其轮廓清晰。该算法能够提升融 合后的医学图像信息量, 同时有效地保护图像的细节信息, 在执行时间和图像质量上均优于普通小波算法。
(A imed at the characterist ics of CT andMR Imedical images, a new image fu sion al2 go rithm based on the fast in t lif t ing w avelet t ran sfo rm s is p ropo sed. Two o riginal images are decompo sed by the fast in t lif t ing w avelet t ran sfo rm s. The fu sion ru le based on the max imum standard deviat ion value variance is u sed to fu se the h igh f requency sub2image, w h ile a w eigh t2 ed average fu sed ru le is app lied by coeff icien t s of the low f requency. F inally, the fu sion image is recon st ructed fo r perfo rm ing inverse fast in t lif t ing w avelet t ran sfo rm s. The fu sion image is evaluated by en t ropy, average gradien t, and co rrelat ion coeff icien t s. Experimen tal resu lt show s that the fu sion image hasmo re info rmat ion than o riginal images and imp roves the quali2 ty of o riginal images. M eanw h ile, the fu sion image p ro tect s detail characterist ics of the image, thu s the real2t ime p rocess and image qualit ies are w ell than tha)