Natural Image Matting

最新推荐文章于 2024-03-06 16:32:57 发布

xlvector

最新推荐文章于 2024-03-06 16:32:57 发布

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分类专栏：图形图像多媒体 Computer Vision 文章标签： image optimization reference google user c

本文链接：https://blog.youkuaiyun.com/xlvector/article/details/1374906

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本文介绍了图像合成中的一项核心任务——抠图(matting)，详细解释了如何从一张包含前景和背景的图片中分离出透明通道(alpha matte)的技术原理。文章探讨了不同抠图方法，包括贝叶斯抠图、泊松抠图、自然图像抠图闭合解及统一抠图与分割迭代优化等。

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Introduction

Composition Image I is generated by foreground and background with alpha matte

I = alpha*F + (1-alpha)*B

Matting is a problem to get alpha,F,B from a given image I.
User have to devide the image into three region: Foreground, Background and Unknown area. In foreground area, F = I, alpha = 1, B = 0; In background area, F = 0, alpha = 0, B = I. Our task is to get F,B,alpha in unknown area.
Consider a point P in unknown area, we have to first estimate F and B in point P.
After estimate F,B in point P, we estimate alpha by minimize a energy:

V = a*V(P) + b*V(P,Q) Q is 4-neighbor of P

V(P) = C - alpha*F - (1-alpha)*B^2

V(P,Q) = alpha(P) - alpha(Q)^2

Result:

Reference (All can be downloaded from Google)

* Y.Chuang, B.Curless, DH.Salesin, R.Szeliski, A Bayesian Approcah to Digital Matting.
* J.Sun, J.Jia, CK.Tang, HY.Shum, Poisson Matting.
* A.Levin, D.Lischinski, Y.Weiss, A Closed Form Solution to Natural Image Matting.
* J.Wang, MF.Cohen, An Iterative Optimization for Unified Image Segmentation and Matting.