At present, the existing evaluation indicators of image fusion algorithms do not in conformity with the standards of human vision system and are not suitable for medical image application scenarios. Therefore, this paper proposes a medical image fusion quality evaluation method combining multi-angle and multi-scale information. We use Gabor Filter to decompose the image and obtain multi-angle texture information, and design a new index, called Multiscale Structural Similarity with Image Resolution (SSIM-IR), to comprehensively evaluate the fused image from edge, structure and sharpness. The experimental results show that this method is more suitable for medical image application scenarios, consistent with subjective evaluation, and can be used for measuring the advantages and disadvantages of medical image fusion algorithm.
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