关键词: 光晕, 梯度反转, 平均亮度, 自适应参数调整, 细节增强

Abstract: In order to solve the phenomenon of halo and gradient inversion caused by guided filtering and the loss of edge of image fusion, this paper proposes a novel improved adaptive multi-exposure image fusion algorithm with guided filtering. Firstly, this paper sets the weight function according to the gradient information in the guided filtering, and combines the image pixel and the mean of the region to create the function, and realizes the adaption of the texture feature of different regions. Secondly, this paper sets the weight function by using the relationship between average brightness and contrast, saturation and exposure moderation, so that the weight value in the weighted average fusion process is no longer a fixed value, and it can adaptively adjust according to different image brightness, values are also different, making the fusion image quality better. Finally, the details of the original sequence map are superimposed on the improved guided filtering image, and the texture detail layer is constructed. The experimental results weaken the halo and gradient inversion phenomena, make the image more real and the details more clear, so the effect of image processing is better. The algorithm is superior to the multi-exposure fusion algorithm and the multi-exposure image fusion of the guided filter, which alleviates the halo phenomenon and obtains the highest 2.5%, 30% and 30% quality improvement respectively in the information entropy, mutual information and edge information evaluation.

Key words: halo, gradient inversion, average brightness, parameter self-adaption, detail enhancement