This paper proposes a Markov random field(MRF) model-based approach to natural image matting with complex scenes.
为了取得更好的抠图效果，提出了一种基于马尔可夫随机场的自然图像抠图方法。
This paper presents an efficient algorithm for alpha estimation based on perceptual color space in natural image matting.
提出一种用于自然图像抠图的高效的基于感知颜色空间的透明度估计方法。
Natural image matting is an important algorithm on image processing to extract the foreground objects from the background image.
所谓复杂图像抠图就是从复杂图像中抠取出目标物体的一种图像处理算法。
The improved color estimate model has better behavior in the natural image matting for the image which the edge color is very different.
实验结果表明，改进后的颜色估计模型在图像边缘附近颜色相差较大的自然景物提取中有较好表现。
To reduce labors such as user input, this paper proposes a simple stroke-based iterative image matting approach, which only needs a few user scribbles to mark foreground and background pixels.
为了获得精确的和视觉上连续的抠图结果，提出了一种基于简单笔画的图像抠图方法，该方法仅需要用户以少量笔画和拖拽矩形框的方式指定前景和背景像素即可实现。
In order to matting image, that is to separate the foreground and background.
实现图像的抠图功能，即把前景和背景分开。
A dynamic environment matting algorithm based on image is developed.
提出了基于图像的动态环境遮片算法。
A dynamic environment matting algorithm based on image is developed.
提出了基于图像的动态环境遮片算法。
应用推荐