Fusion image quality evaluation method for infrared and visible light images

Abstract

The invention discloses a fusion image quality evaluation method for infrared and visible light images. The method comprises the steps of acquiring an infrared source image, a visible light source image and a fusion image; based on the gradient amplitude information entropy of the fusion image, calculating the global detail characteristic index of the fusion image; dividing the infrared source image into a target region and a background region by adopting the salient region extraction method of the frequency domain, and mapping the division result to the fusion image; respectively calculating the edge structure similarity between the target region of the infrared image and the target region of the fusion image, and the contrast between the target and the background of the fusion image, and calculating the sum of the above obtained results to obtain the local target characteristic index of the fusion image; finally, subjecting the global detail characteristic index of the fusion image and the local target characteristic index of the fusion image to weighted summation so as to obtain the fusion image quality evaluation index of infrared and visible light images. According to the invention, the global detail features and the local target features of the fusion image can be evaluated, while the overall features of the fusion image can also be evaluated. Both the universality requirement and the particularity requirement during the actual evaluation process are taken into consideration. Therefore, the method is high in consistency with the subjective evaluation.

Description

technical field [0001] The invention relates to the field of image fusion quality evaluation, in particular to an infrared and visible light image fusion quality evaluation method. Background technique [0002] Infrared and visible light image fusion is an important branch of image fusion, and it is also the focus of current image fusion research. Infrared sensors image through thermal radiation, which is helpful to highlight the target area in the scene, but cannot characterize the details of the scene well; visible light sensors can provide detailed information about the scene where the target is located through imaging through object reflection. Therefore, the fusion of infrared and visible light images not only has good target characteristics of infrared images, but also preserves the details of visible light images well. Compared with the rapidly developing image fusion technology, the development of fusion image quality evaluation is relatively slow. Image fusion qua...

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Problems solved by technology

[0006] 1. Both of the above two technologies evaluate the quality of the fusion image by calculating the similarity between the source image and the fusion image, and both of these two technologies ignore the details of the fusion image itself;

[0007] 2. One of the main purposes of infrared and visible light image fusion is to preserve the target features of the infrared source image, but neither of the above two techniques evaluates the target features of the fused image;

[0008] 3. A method and device for image fusion quality evaluation (Chinese Patent Document No. CN103049893A) uses fuzzy clustering method to segment infrared images, but this segmentation method cannot correctly segment images with complex background interference and low signal-to-noise ratio images, which affects subsequent evaluation results;

However, when the two images are blurred, the image fusion quality evaluation results obtained by applying these two techniques respectively have poor consistency with the subjective evaluation.

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