改进的自然图像鲁棒抠图算法

自然抠图从背景复杂的彩色图像中根据已知像素进行未知像素的透明度估计以实现前景的准确提取，是图像处理和影视制作的关键技术之一。由于自然图像透明度值的求解具有高度不确定性，目前对颜色和结构复杂的图像抠图效果并不理想。提出一种改进的鲁棒抠图算法。该方法根据trimap的已知前景和背景区域减少未知像素个数；计算前景-背景对的可靠性，选择可信赖的样本对获得透明度的初始值和信心值；优化基于图拉普拉斯的二次目标函数并确定未知像素最终透明度值。自然抠图实验结果表明，与几种主要抠图算法相比，所提方法能提取到具有更好视觉效果和均方误差的前景。

Improved robust matting algorithm for nature image

Alpha matting, aiming at extraction of foreground elements from a natural image by means of opacity（alpha）estimation, is one of the key techniques for image editing and film production. However, matting is inherently an ill-posed problem. Many matting approaches perform poorly with the complex natural images. An improved robust matting algorithm is proposed. The proposed method involves labeling some unknown pixels according to the known regions of trimap, selection of foreground and background pairs for unknown pixels to determine of the initial alpha and its confidence, optimization of the initial alpha by minimizing the quadratic object function based on matte Laplacian. The experiments on the benchmark images are carried out and the results show that the proposed method performs better in the qualitative and quantitative comparison with some popular matting algorithms.