Abstract: The image foreground extraction is using image processing algorithms to quickly and accurately extract the target image that people are interested in. The precision of image foreground extraction directly affects the subsequent processing of target image. In order to improve the accuracy of image foreground extraction, this paper proposes a new Poisson matting algorithm using global method. In order to improve the speed, this paper uses a diffusion-search method, and analyzes the effectiveness and accuracy of the algorithm. Diffusion method is to find the least cost sampling points by calculating the cost of each sampling point in a small neighborhood, it can obtain the optimal solution adjacent areas; Search method is to find the optimal sampling point by certain rules, it can accelerate the speed to find the optimal sampling point. Finally, the experiment proves that Poisson extraction algorithm based on global foreground will get more accurate results for foreground extraction.

Key words: Poisson algorithm, foreground extraction, global algorithm

摘要： 图像前景提取是运用图像处理算法快速准确地提取出图像中人们感兴趣的目标。图像前景提取的精度直接影响了对目标图像的后续处理。为了提高图像前景提取的精度，提出了一个新的利用全局方法进行Poisson前景提取的算法。为了能够更快更好地得到最优采样点，提出了扩散、搜索的方法，并对该方法的有效性和精确性进行了分析。扩散方法是通过在较小的邻域内计算各采样点的代价寻找代价最小的采样点，它能够得到邻近区域的最优解；搜索方法是通过一定的规则跳跃式地寻找最优采样点，它能够加快寻找最优采样点的速度。实验表明，基于全局的Poisson前景提取算法会得到更精确的前景提取结果。

关键词: 泊松算法, 前景提取, 全局算法