粗糙集理论在图像处理中的应用

Rough Set Theory and Its Applications in Image Processing

将粗糙集理论应用到图像处理中,在很多场合具有比传统方法和精确算法更好的效果。介绍了粗糙集理论的基本概念和模型的发展状况,描述了粗糙集用于图像处理的特点,详细论述了粗糙集理论在图像滤波和平滑、图像增强、图像分割以及图像特征提取与分类的研究方法与应用。研究表明粗糙集理论与其他智能方法的结合在图像处理中具有良好的应用前景。大数据集、高效约简算法、并行计算以及混合智能算法研究等问题仍是粗糙集研究的主要方向。

In order to reach better results than traditional methods and accurate algorithms, rough sets is induced in image processing. The basic concepts in rough sets and development of rough sets models are introduced. The characteristics are suited for image processing. The applications of rough sets for image filter, image enhancement, image segmentation, feature extraction and classification are described detailed. It shows the hybrid methods combined rough sets and other intelligent methods are used to result in better performance in image processing field. The research for large data sets, highly effective reduets algorithms, parallel algorithms and hybrid intelligent methods is still main direction for rough sets.