Selective Light Field Refocusing for Camera Arrays Using Bokeh Rendering and Superresolution
This work addresses the need for high-quality post-capture refocusing in camera arrays, offering incremental improvements in visual performance and depth-of-field adjustment.
The paper tackles the problem of improving imaging quality in camera arrays by proposing a selective light field refocusing method that superresolves focused regions and aesthetically renders bokeh, achieving superior visual performance with acceptable computational cost compared to state-of-the-art methods.
Camera arrays provide spatial and angular information within a single snapshot. With refocusing methods, focal planes can be altered after exposure. In this letter, we propose a light field refocusing method to improve the imaging quality of camera arrays. In our method, the disparity is first estimated. Then, the unfocused region (bokeh) is rendered by using a depth-based anisotropic filter. Finally, the refocused image is produced by a reconstruction-based superresolution approach where the bokeh image is used as a regularization term. Our method can selectively refocus images with focused region being superresolved and bokeh being aesthetically rendered. Our method also enables postadjustment of depth of field. We conduct experiments on both public and self-developed datasets. Our method achieves superior visual performance with acceptable computational cost as compared to other state-of-the-art methods. Code is available at https://github.com/YingqianWang/Selective-LF-Refocusing.