Sun Menghui, Zhu Xiaoliang, Niu Yunzhen, Li Yang, Wen Mengke
School of Software, Xinjiang University, Ürümqi, 830008, China.
Affiliated Tumor Hospital, Xinjiang Medical University, Ürümqi, 830011, China.
Curr Med Imaging. 2024;20:e15734056325441. doi: 10.2174/0115734056325441241022085037.
Currently, most multimodal medical image fusion techniques focus solely on integrating the edge details of image features, often overlooking color preservation from the source images. Hence, this paper proposes a multi-channel fusion algorithm based on gradient domain-guided image filtering.
This study aims to enhance the color preservation of source images in multimodal medical image fusion algorithms.
Utilizing gradient field-guided image filters for image smoothing, the process involves constructing different image layers, decomposing using wavelet transforms, and downsampling. Various fusion rules are then applied before inverse wavelet transformation.
Regarding MSE, CCI, PSNR, SSIM, DD, SM, and other metrics, the proposed algorithm consistently ranks highest compared to alternative methods.
Through both subjective and objective analyses, experimental results substantiate the significant edge-preserving effects of the proposed fusion algorithm while effectively maintaining image fidelity and spectral integrity.
目前，大多数多模态医学图像融合技术仅专注于整合图像特征的边缘细节，常常忽略源图像的颜色保留。因此，本文提出了一种基于梯度域引导图像滤波的多通道融合算法。
本研究旨在增强多模态医学图像融合算法中源图像的颜色保留。
利用梯度场引导图像滤波器进行图像平滑，该过程包括构建不同的图像层、使用小波变换进行分解以及下采样。然后在小波逆变换之前应用各种融合规则。
在均方误差（MSE）、相关系数指数（CCI）、峰值信噪比（PSNR）、结构相似性指数（SSIM）、差异度（DD）、相似度（SM）等指标方面，与其他方法相比，所提出的算法始终排名最高。
通过主观和客观分析，实验结果证实了所提出的融合算法具有显著的边缘保留效果，同时有效地保持了图像保真度和光谱完整性。
