基于小波变换的GrabCut图像分割

研究 GrabCut 是以迭代能量优化算法为基础，以颜色和纹理为特征，从背景图像中提取出目标的图像分割算法。但该方法速度较慢，为了达到实时应用的目的，提出了一种基于小波变换的 GrabCut 图像分割方法。该方法首先对原始图像进行小波变换的图像压缩，使得原始图像的分辨率降低，然后在压缩后的图像上迭代GrabCut算法，最后将收敛获得的目标区域作为原始图像初始值，再次使用GrabCut算法在原始图像上进行迭代，从而提取出目标。实验结果证明该算法提高了图像目标的提取速度，并保持图像目标的特征基本不变。

GrabCut Image Segmentation Based on Wavelet Transsform

GrabCut is an algorithm based on the energy optimization algorithm. It uses color and texture features to extract the target from the background image. However, the processing speed of this method is slower than we expect. In order to accelerate the image segmentation, this paper presents a GrabCut image segmentation method based on wavelet transform. The proposed method compress the original image based on wavelet transform to reduce the image resolution and applies the GrabCut algorithm on it. Then identify the initial value of the original image with the convergent target area, and the algorithm applies the last GrabCut iteration on original image. Experimental results show that the algorithm improves the extraction rate of the target image, and keeps the basic characteristics of the target image unchanged.