Multisequence exposure image fusion method based on weight function

Aiming at the existing multi-exposure image fusion method based on weight function, the fused image obtained tends to introduce halo artifacts, loss of details, unclear edges and other problems. A multi-exposure image fusion method with improved weight function is proposed. First, the luminance weights reflecting the importance of each pixel of the image to the global luminance and neighboring exposure images are determined, and the gradient weights reflecting the importance of the local gradient of each pixel in the whole sequence of the image are determined, and the contrast weights are used to improve the clarity and detail information of the integration results; finally, the fused images are obtained according to the weights. According to the experimental results that the image fusion effect of the method proposed in this paper is clear and natural, and the average multi-exposure fusion structural similarity (MEF-SSIM) reaches 0.981, and the average running time is 0.725s.