Geometric Scene Refocusing
This work provides a new method for geometrically correct post-capture refocusing, which is significant for photographers and computer vision applications dealing with shallow depth-of-field images, offering improved fidelity in focus and defocus blur preservation.
This paper addresses the challenge of representing and manipulating images with shallow depth-of-field, specifically within focal stacks. It introduces a novel representation that combines existing focus measures to identify various pixel types (in-focus, dual-focus, bokeh) and spatially-varying blur kernels, enabling high-fidelity post-capture refocusing.
An image captured with a wide-aperture camera exhibits a finite depth-of-field, with focused and defocused pixels. A compact and robust representation of focus and defocus helps analyze and manipulate such images. In this work, we study the fine characteristics of images with a shallow depth-of-field in the context of focal stacks. We present a composite measure for focus that is a combination of existing measures. We identify in-focus pixels, dual-focus pixels, pixels that exhibit bokeh and spatially-varying blur kernels between focal slices. We use these to build a novel representation that facilitates easy manipulation of focal stacks. We present a comprehensive algorithm for post-capture refocusing in a geometrically correct manner. Our approach can refocus the scene at high fidelity while preserving fine aspects of focus and defocus blur.