基于多层次多方向分解的医学图像融合算法
传统多模态医学图像融合技术融合后图像的细节表达不清晰、病灶不明显。为此，设计一种V-变换与非下采样Contourlet变换（NSCT）相结合的融合方法。对源图像进行多层次V-分解，使其被分解为轮廓图像和细节图像两部分，对其中的轮廓图像做NSCT变换，在NSCT域中设计融合方案，针对细节图像给出细节信息的融合策略，将融合后的轮廓图像和细节图像叠加，以得到最终融合图像。实验结果表明，与传统离散小波变换、NSCT变换的方法相比，该算法在视觉效果和评价指标方面都有较好的表现。...
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| Published in | 计算机工程 Vol. 43; no. 10; pp. 179 - 185 |
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| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
北方工业大学理学院,北京,100144%北京林业大学理学院,北京,100083%澳门科技大学资讯科技学院,澳门,999078
2017
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1000-3428 |
| DOI | 10.3969/j.issn.1000-3428.2017.10.030 |
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| Summary: | 传统多模态医学图像融合技术融合后图像的细节表达不清晰、病灶不明显。为此，设计一种V-变换与非下采样Contourlet变换（NSCT）相结合的融合方法。对源图像进行多层次V-分解，使其被分解为轮廓图像和细节图像两部分，对其中的轮廓图像做NSCT变换，在NSCT域中设计融合方案，针对细节图像给出细节信息的融合策略，将融合后的轮廓图像和细节图像叠加，以得到最终融合图像。实验结果表明，与传统离散小波变换、NSCT变换的方法相比，该算法在视觉效果和评价指标方面都有较好的表现。 |
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| Bibliography: | SONG Ruixia1, WANG Meng1 , WANG Xiaochun2 , YU Jiande3 （ 1. College of Science,North China University of Technology, Beijing 100144, China ; 2. School of Science, Beijing Forestry University, Beijing 100083, China ; 3. Faculty of Information Technology ,Macau University of Science and Technology, Macao 999078, China） 31-1289/TP image fusion; medical image; V-system; multi-layer V-decomposition; Non-subsampled ContourletTransform （NSCT） Fused images obtained using the traditional multi-modal medical image fusion technology cannot express details clearly and lesion obviously. In view of this, a new fusion method which combines the V-transform and Non- subsampled Contourlet Transform（NSCT） is proposed. The source images are first decomposed into contour sub-image and detail sub-images by applying the multi-layer V-decomposition, and then NSCT transform is performed on the contour sub-image. Fusion rule in NSCT domain is designed. Fusion strategy for detail information is presented on detail sub-images. The fused im |
| ISSN: | 1000-3428 |
| DOI: | 10.3969/j.issn.1000-3428.2017.10.030 |