CAJ | 학술논문

在图像处理中，分割算法是其主要研究焦点之一。针对该问题，提出基于信息瓶颈法的新图像分离-合并分割算法。该方法的目的是抽取与输入相关的一个变量的紧密表征，并使得在考虑与输出相关的另一个变量互信息的损失最小。首先，基于一系列图像区域和强度直方图集合之间定义信息渠道，在此渠道中，以互信息的最大化来优化图像分割法；然后，通过最小化互信息损失，完成在上一阶段中获得的多区域合并过程。在二维图像上做的实验表明所提出算法的性能。
재도상처리중，분할산법시기주요연구초점지일。침대해문제，제출기우신식병경법적신도상분리-합병분할산법。해방법적목적시추취여수입상관적일개변량적긴밀표정，병사득재고필여수출상관적령일개변량호신식적손실최소。수선，기우일계렬도상구역화강도직방도집합지간정의신식거도，재차거도중，이호신식적최대화래우화도상분할법；연후，통과최소화호신식손실，완성재상일계단중획득적다구역합병과정。재이유도상상주적실험표명소제출산법적성능。
In image processing, segmentation algorithms constitute one of the main focuses of research .In this paper, new image split-and-merge segmentation algorithms based on a hard version of the information bottleneck method are presented .The objective of this method is to extract a compact representation of a variable , considered the input , with minimal loss of mutual information with respect to another variable , considered the output .First, the algorithm is based on the definition of an information channel between a set of regions (input) of the image and the intensity histogram bins (output).From this channel, the maximization of the mutual information gain is used to optimize the image partitioning .Then, the merging process of the regions obtained in the previous phase is carried out by minimizing the loss of mutual information .Different experiments on 2-D images show the behavior of the proposed algorithm .