Compared to traditional 2D images, light field images record both spatial and angular information of the scene, which can provide more data for image fusion. In this paper, a light field all-in-focus image fusion algorithm based on spatially-guided angular information is proposed. In the proposed method, the initial weight maps carrying the angular information are calculated by comparing the block variance of the 4D light field data. The initial weight maps are then guided by digital refocused images carrying the spatial information to obtain the refined weight maps. In the refocused image multi-scale decomposition, the micro-lens calibration error is considered and the additional edge layers are extracted to suppress the edge artifacts. Experiments demonstrate the effectiveness of the proposed algorithm. Quantitative evaluation results show that the proposed algorithm performs the best in the feature-based index and structural similarity-based index without sacrificing the information and perceptual sharpness of the fused image.

与传统的2D图像相比，光场图像记录场景的空间和角度信息，可以为图像融合提供更多数据。提出了一种基于空间导引角信息的光场全焦点图像融合算法。在所提出的方法中，通过比较4D光场数据的块方差来计算携带角度信息的初始权重图。然后，通过携带空间信息的数字重聚焦图像引导初始权重图，以获得精确的权重图。在重新聚焦的图像多尺度分解中，考虑了微透镜校准误差，并提取了额外的边缘层以抑制边缘伪影。实验证明了该算法的有效性。