基于LDC的图像过渡区提取与分割

摘要

A novel algorithm for the image transition region extraction and segmentation is presented based on local definition-complexity of the image. At first,the local definition of the original image is calculated to get a definition image, which enhanced the transition region's grey level. Then the local complexity of the definition image is calculated and transition region extraction threshold is gotten based on the complexity curve. At last,segmentation is made to the original image according to the threshold value obtained from the extracted transition region histogram. Experiment results demonstrate that the proposed algorithm achieves a better transition region extraction and segmentation performance.%提出一种基于局部清晰度-复杂度的图像过渡区提取算法,通过计算图像局部清晰度获得清晰度图像,增加了过渡区灰度层次信息,再计算清晰度图像的局部复杂度,并根据复杂度曲线确定过渡区提取门限对过渡区进行提取,根据提取的过渡区灰度直方图,获得图像的分割阈值并对图像进行分割.实验结果表明,本文方法比传统的基于局部复杂度法提取的过渡区更加准确,图像分割效果更好.