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L0 smoothing based detail enhancement for fusion of differently exposed images

机译:基于L0平滑的细节增强功能可融合不同曝光的图像

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Exposure fusion is a technique to fuse several differently exposed low dynamic range (LDR) images to an LDR image. The output image has more information than each of the input images, but it could suffer from loss of fine details. In this paper, we propose a detail-enhanced exposure fusion algorithm by introducing an L0 norm based optimization in gradient domain. The proposed algorithm extracts fine details from a vector field that is generated by using the gradient fields of the input images and adds the fine details to an intermediate image that is fused by an existing exposure fusion algorithm. Experimental results prove that the proposed method can enhance fine details for fused images.
机译:曝光融合是一种将多个不同曝光的低动态范围(LDR)图像融合到LDR图像的技术。输出图像比每个输入图像具有更多的信息,但是可能会丢失细节。在本文中,我们通过引入基于L 0 范数的梯度域优化来提出一种细节增强的曝光融合算法。所提出的算法从通过使用输入图像的梯度场生成的矢量场中提取精细细节,并将精细细节添加到由现有的曝光融合算法融合的中间图像上。实验结果证明,该方法可以提高融合图像的精细度。

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