Image fusion method based on brightness self-adaption and significance detection

Abstract

The invention discloses an image fusion method based on brightness self-adaption and significance detection. The method comprises the following steps: collecting an infrared image and a visible lightimage, and respectively carrying out image preprocessing and image registration; determining a brightness level by using histograms of the infrared image and the visible light image after graying processing, counting image pixel significance values and calculating a brightness weight; carrying out image decomposition by utilizing a rolling guided filtering method; defining pixel saliency values, and combining the plurality of pixel saliency values into a saliency map; carrying out fusion of a base layer image and fusion of a detail layer image; and superposing the base layer fusion image and the detail layer fusion image to obtain a final image fusion result. According to the method, the image brightness is graded, the to-be-fused image is decomposed based on rolling guided filtering, global targets and details of the image are processed separately, the brightness weight and the saliency map are used for fusing the base layer image, the least square method is used for fusing the detaillayer image, and the image fusion effect is improved.

Description

technical field [0001] The present invention relates to the field of image fusion, more specifically, to an image fusion method based on brightness self-adaptation and saliency detection. Background technique [0002] With the rise of artificial intelligence, visual image processing has a wide range of applications in robotics. It can perform scene recognition and positioning through matching and distance calculations, and then use the processing results of image data for robot control. However, due to the imaging principle of visible light cameras, vision sensors often have certain application limitations: (1) cannot adapt to complex environmental applications, such as strong exposure scenes or complex backgrounds, and are usually only used in simple and bright scenes; (2) traditional image The processing cannot judge whether the change in the gray value of the image is due to the change of the scene or the difference caused by the change of light in the same scene, so it c...

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