一类新的基于一维renyi熵的图像分割迭代算法

A New Class of Image Segmentation Iterative Algorithm Based on One-dimensional Renyi Entropy

针对一维renyi熵算法的局限性,利用一维renyi熵算法的阈值,提出了一个新的迭代算法。其不断地寻找分割原始图像的子区域,当相邻两次迭代计算出的阈值之差小于一个预设常数时就停止迭代,并且把最后一次迭代得到的阈值作为最终分割阈值。文中不但给出了直观的分割结果,而且运用均匀性测度这一图像分割评价指标给出了分割效果的量化结果。实验表明,所提出的方法不但从直观上达到了较理想的分割效果,而且在整个迭代过程中计算出的均匀性测度呈单调递增的趋势。同时,实验验证了该算法对参数α的不敏感性。

Aiming at the limitation of one-dimensional renyi entropy algorithm,the paper proposed a new iterative method in image segmentation based on one-dimensional renyi＇s threshold.The method iteratively searches for sub regions of the image for segmentation for processing to get the final segmentation threshold.The process stops when the renyi＇s thresholds calculated between two iterations is less than a preset constantand the last threshold calculated is the final threshold that we want.The paper not only gave the segmentation result intuitively but also gave the quantitative result of segmentation using the uniformity measure which is an image segmentation evaluation criteria.The experiment results show that the iterative method not only can get desired segmentation result intuitively but also that the uniformity measure calculated at each iteration is a monotone increasing sequence.And the experiment shows that the proposed method is not sensitive to parameterα.