Digital refocusing has a tradeoff between complexity and quality when using sparsely sampled light fields for low-storage applications. In this paper, we propose a fast physically correct refocusing algorithm to address this issue in a twofold way. First, view interpolation is adopted to provide photorealistic quality at infocus-defocus hybrid boundaries. Regarding its conventional high complexity, we devised a fast line-scan method specifically for refocusing, and its 1D kernel can be 30× faster than the benchmark View Synthesis Reference Software (VSRS)-1D-Fast. Second, we propose a block-based multi-rate processing flow for accelerating purely infocused or defocused regions, and a further 3- 34× speedup can be achieved for high-resolution images. All candidate blocks of variable sizes can interpolate different numbers of rendered views and perform refocusing in different subsampled layers. To avoid visible aliasing and block artifacts, we determine these parameters and the simulated aperture filter through a localized filter response analysis using defocus blur statistics. The final quadtree block partitions are then optimized in terms of computation time. Extensive experimental results are provided to show superior refocusing quality and fast computation speed. In particular, the run time is comparable with the conventional single-image blurring, which causes serious boundary artifacts.

Digital refocusing for sparsely sampled light fields results in aliasing effect. For realistic quality, previous works performed anti-aliasing by applying time-consuming view interpolation for a heuristic number of novel views. In this paper, we study this problem by first performing a spectral analysis to give an analytical rule for the novel view number, which saves 34% of views compared to the intuitional choice. Then we propose a fast refocusing algorithm using a view interpolation method which is about 30x faster than VSRS-1D-Fast. Experimental results show the effectiveness of our approach in terms of speed and quality. For showing realistic refocusing, a light-field wafer-level-optics array is implemented, and its refocused images are compared to pictures captured by a real camera.