基于自适应对偶字典的磁共振图像的超分辨率重建

基于自适应对偶字典的磁共振图像的超分辨率重建
佚名
【期刊名称】《光电技术应用》
【年(卷),期】2013(000)004
【摘要】为了提高磁共振成像的图像质量，提出了一种基于自适应对偶字典的超
分辨率去噪重建方法，在超分辨率重建过程中引入去噪功能，使得改善图像分辨率的同时能够有效地滤除图像中的噪声，实现了超分辨率重建和去噪技术的有机结合。

该方法利用聚类—PCA算法提取图像的主要特征来构造主特征字典，采用训练方
法设计出表达图像细节信息的自学习字典，两者结合构成的自适应对偶字典具有良好的稀疏度和自适应性。

实验表明，与其他超分辨率算法相比，该方法超分辨率重建效果显著，峰值信噪比和平均结构相似度均有所提高。

%In order to enhance images quality of magnetic resonance imaging (MRI), a super-resolution
de⁃noising reconstruction method is proposed based on adaptive dual dictionary. In the method, denoising function is used in super-resolution reconstruction process so that the noise in images is filtered effectively as the improve⁃ment of image resolution. And the integration of super-resolution reconstruction and denoising technology is im⁃plemented. Clustering-PCA algorithm is used in the method to extract main features of images to construct main-feature dictionary. Training method is used to design self-learning dictionary expressing detailed informa⁃tion of images. Adaptive dual dictionary constructed by combination of the two dictionaries has good sparseness and adaptability. Experimental results
show that super-resolution reconstruction effect is remarkable in the meth⁃od comparing with other super-resolution algorithms. Peak signal to noise ratio (PSNR) and mean structure simi⁃larity (MSSIM) are all improved.【总页数】6页(P55-60)
【正文语种】中文
【中图分类】R445.2
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