Entropy based bi-region image segmentation
基于熵的两区域图像分割

Image segmentation plays an important part in the areas of multimedia, image processing and computer vision. In the paper, the authors propose an image segmentation approach based on an entropy measurer. Specifically, the image segmentation entropy (ISE) is defined to describe the information of an image region. We further prove that the image after segmentation have the minimum ISE, if the image is correctly partitioned. Then, the image segmentation problem is cast into an optimization problem which minimizes ISE. Finally, we use the iterative graph cut approach (IGCA) to solve the optimization problem. The experiments provided in the paper show that our ISE based segmentation approach works well.