Hierarchical and Progressive Image Matting

Grayscale Image Matting and Colorization

This paper presents a novel approach to grayscale image matting and colorization. The first part of this approach is an efficient grayscale image matting algorithm in Bayesian framework. The foreground and background color distributions, and the alpha’s distribution are modelled with spatially varying sets of Gaussians. The major novelties of this matting algorithm are the introduction of alpha...

Interactive Image Matting using Optimization

In this paper, we formulate interactive image matting as a constrained optimization problem. We first make some simple and reasonable assumptions about the alpha matte and assume that, geometrically, the closer two pixels are, the more likely they will have similar alpha values, conversely, the farther apart two pixels are, the more likely they will have different alpha values; photometrically,...

Confidence-driven image co-matting

Single image matting, the task of estimating accurate foreground opacity from a given image, is a severely ill-posed and challenging problem. Inspired by recent advances in image co-segmentation, in this paper, we present a novel framework for a new task called co-matting, which aims to simultaneously extract alpha mattes in multiple images that contain slightly-deformed instances of the same f...

Towards Efficient and Accurate Image Matting

Image and Video Matting: A Survey

Matting refers to the problem of accurate foreground estimation in images and video. It is one of the key techniques in many image editing and film production applications, thus has been extensively studied in the literature. With the recent advances of digital cameras, using matting techniques to create novel composites or facilitate other editing tasks has gained increasing interest from both...