Incomplete multi-modal brain image fusion for epilepsy classification

Zhu, Qi; Li, Huijie; Ye, Haizhou; Zhang, Zhiqiang; Wang, Ran; Fan, Zizhu; Zhang, Daoqiang

doi:10.1016/j.ins.2021.09.035

Cited by 10 publications

(1 citation statement)

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Image fusion is an image enhancement technology, whose goal is to synthesize and process multi-source images of the same scene from different types of sensors, so as to generate result images with richer information and more robust performance that can better assist the completion of the next task [1][2][3][4]. Image fusion technology has been widely used in the fields of remote sensing engineering and medical engineering since its birth [5,6]. At the same time, the research of image fusion algorithm has also attracted the attention of more and more scholars.

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confidence: 99%

Image fusion research based on the Haar-like multi-scale analysis

Zhu,

Wen

2024

EURASIP J. Adv. Signal Process.

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In view of the serious color and definition distortion in the process of the traditional image fusion, this study proposes a Haar-like multi-scale analysis model, in which Haar wavelet has been modified and used for the medical image fusion to obtain even better results. Firstly, when the improved Haar wavelet basis function is translated, inner product and down-sampled with each band of the original image, the band is decomposed into four sub-images containing one low-frequency subdomain and three high-frequency subdomains. Secondly, the different fusion rules are applied in the low-frequency domain and the high-frequency domains to get the low-frequency sub-image and the high-frequency sub-images in each band. The four new sub-frequency domains are inverse-decomposed to reconstruct each new band. The study configures and synthesizes these new bands to produce a fusion image. Lastly, the two groups of the medical images are used for experimental simulation. The Experimental results are analyzed and compared with those of other fusion methods. It can be found the fusion method proposed in the study obtain the superior effects in the spatial definition and the color depth feature, especially in color criteria such as OP, SpD, CR and SSIM, comparing with the other methods.

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confidence: 99%