期刊
IEEE TRANSACTIONS ON IMAGE PROCESSING
卷 26, 期 12, 页码 5855-5866出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIP.2017.2745202
关键词
Image fusion; multi-scale decomposition; interest-based rule
资金
- Natural Science Foundation of China [61272195, 61472055, U1401252]
- Chongqing Outstanding Youth Fund [cstc2014jcyjjq40001]
- Chongqing Research Program of Application Foundation and Advanced Technology [cstc2012jjA1699]
A novel method for performing anatomical magnetic resonance imaging-functional (positron emission tomography or single photon emission computed tomography) image fusion is presented. The method merges specific feature information from input image signals of a single or multiple medical imaging modalities into a single fused image, while preserving more information and generating less distortion. The proposed method uses a local Laplacian filtering-based technique realized through a novel multi-scale system architecture. First, the input images are generated in a multi-scale image representation and are processed using local Laplacian filtering. Second, at each scale, the decomposed images are combined to produce fused approximate images using a local energy maximum scheme and produce the fused residual images using an information of interest-based scheme. Finally, a fused image is obtained using a reconstruction process that is analogous to that of conventional Laplacian pyramid transform. Experimental results computed using individual multi-scale analysis-based decomposition schemes or fusion rules clearly demonstrate the superiority of the proposed method through subjective observation as well as objective metrics. Furthermore, the proposed method can obtain better performance, compared with the state-of-the-art fusion methods.
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