Method and device for evaluating image fusion quality
A quality evaluation and image fusion technology, applied in the field of image fusion, to avoid image blur and noise, high consistency, and good quality.
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Embodiment 1
[0048] figure 1 The implementation process of the image fusion quality evaluation method provided in the first embodiment of the present invention is shown. The process of the method is described in detail as follows:
[0049] In step S101, each source image and a fusion image of the source image are acquired;
[0050] In step S102, each source image is segmented using a fuzzy clustering method to obtain segmented images, and the segmented images of each source image are merged into a total segmentation map;
[0051] In step S103, obtain a visual saliency map and a variance saliency map of each source image, and merge the visual saliency map and the variance saliency map into a visual variance saliency map;
[0052] In step S104, a weight map is calculated according to the visual variance saliency map, and a saliency coefficient of each region of the source image and the fusion image is calculated according to the visual variance saliency map and the total segmentation map;
[0053] In ...
Embodiment 2
[0095] Image 6 The composition structure of the image fusion quality evaluation device provided in the second embodiment of the present invention is shown. For ease of description, only the parts related to the embodiment of the present invention are shown.
[0096] The image fusion quality evaluation device may be a software unit, a hardware unit or a combination of software and hardware running in each application system.
[0097] The image fusion quality evaluation device includes an image acquisition unit 61, an image segmentation unit 62, a saliency map acquisition unit 63, a first calculation unit 64, a second calculation unit 65, and an index acquisition unit 66, and its specific functions are as follows:
[0098] The image acquisition unit 61 is configured to acquire each source image and a fusion image of the source image;
[0099] The image segmentation unit 62 is configured to segment each source image by using a fuzzy clustering method to obtain segmented images, and merge...
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