论文标题
用于多帧暴露融合的空间变体拉普拉斯金字塔
Spatially Variant Laplacian Pyramids for Multi-Frame Exposure Fusion
论文作者
论文摘要
Laplacian金字塔混合是一种常用的方法，用于几种无缝的图像混合任务。尽管该方法适用于具有可比强度水平的图像，但通常无法为处理具有较大强度变化（例如曝光融合）的图像的应用产生无伪影的图像。本文提出了在空间上变化的拉普拉斯金字塔混合物，以将图像混合具有较大的强度差异。提出的方法根据局部强度变化的量，在金字塔重建的最后阶段动态改变了混合水平。所提出的算法输出执行了最新的方法，以定性地融合图像，并在公开可用的高动态范围（HDR）成像数据集上进行定量。在细节，光环和黑暗光晕方面，证明了定性的改进。为了进行定量比较，使用了No-Reference MEF-SSIM。
Laplacian Pyramid Blending is a commonly used method for several seamless image blending tasks. While the method works well for images with comparable intensity levels, it is often unable to produce artifact free images for applications which handle images with large intensity variation such as exposure fusion. This paper proposes a spatially varying Laplacian Pyramid Blending to blend images with large intensity differences. The proposed method dynamically alters the blending levels during the final stage of Pyramid Reconstruction based on the amount of local intensity variation. The proposed algorithm out performs state-of-the-art methods for image blending both qualitatively as well as quantitatively on publicly available High Dynamic Range (HDR) imaging dataset. Qualitative improvements are demonstrated in terms of details, halos and dark halos. For quantitative comparison, the no-reference perceptual metric MEF-SSIM was used.
