Multi-modal Medical Image Fusion Approach Utilizing Gradient Domain Guided Image Filtering

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.