Fast Multi-Level Foreground Estimation
This work addresses a specific bottleneck in image editing workflows for users needing efficient foreground estimation, though it is incremental as it builds on existing alpha matting methods.
The paper tackles the problem of foreground color estimation in alpha matting, which is often neglected despite being essential for image editing, and shows that their fast multi-level method achieves results comparable to state-of-the-art while significantly improving computational runtime and memory usage.
Alpha matting aims to estimate the translucency of an object in a given image. The resulting alpha matte describes pixel-wise to what amount foreground and background colors contribute to the color of the composite image. While most methods in literature focus on estimating the alpha matte, the process of estimating the foreground colors given the input image and its alpha matte is often neglected, although foreground estimation is an essential part of many image editing workflows. In this work, we propose a novel method for foreground estimation given the alpha matte. We demonstrate that our fast multi-level approach yields results that are comparable with the state-of-the-art while outperforming those methods in computational runtime and memory usage.