改进的二维Renyi熵图像阈值分割

Image Threshold Segmentation Based on Improved Two-dimensional Renyi Entropy

提出一种基于灰度-梯度信息二维Renyi熵图像阈值分割新方法。首先,由图像灰度值和梯度值构造出二维直方图,在此基础上计算目标和背景区域的二维Renyi熵,并使此熵值函数最大,得到分割阈值。像素梯度信息和Re-nyi熵可调参数相结合,可以处理更多类型的图像,同时分割得到的图像内部更均匀,边界形状更准确。

This paper presented a new image threshold segmentation method based on improved two-dimensional Renyi entropy.First,two-dimensional histogram was build according to gray value and gradient value of the pixels,on this basis,calculated two-dimensional Renyi entropy of target and Background region,at last,we got segmentation threshold by maximizing the Renyi entropy function.It can handle more types of images and get more accurate shape of the image edge that pixels gradient information in combination with parameter of Renyi entropy which is adjustable.