Selective Light Field Refocusing for Camera Arrays Using Bokeh Rendering and Superresolution

TL;DR

This paper introduces a novel light field refocusing technique for camera arrays that enhances image quality by combining disparity estimation, depth-based bokeh rendering, and superresolution, enabling selective refocusing and post-adjustment of depth of field.

Contribution

It presents a new method that improves light field refocusing by integrating anisotropic filtering and superresolution, offering better visual quality and flexibility over existing approaches.

Findings

Achieves superior visual quality compared to state-of-the-art methods.

Enables post-adjustment of depth of field.

Maintains acceptable computational cost.

Abstract

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.