CAJ | 학술논문

针对传统滤波器在噪声检测和滤除中存在的不足，提出了基于商空间粒度理论的噪声检测和粒度逆谐波均值滤波算法。该算法将受噪声污染的图像划分成不同粒度层次的商空间，形成商空间半序格，结合保假原理选择适当的粒度空间实施噪声分类检测和分别滤除。实验结果表明，该算法在滤除噪声的同时能够较好地保持图像的细节纹理特征、改善图像质量、提高信噪比等。
침대전통려파기재조성검측화려제중존재적불족，제출료기우상공간립도이론적조성검측화립도역해파균치려파산법。해산법장수조성오염적도상화분성불동립도층차적상공간，형성상공간반서격，결합보가원리선택괄당적립도공간실시조성분류검측화분별려제。실험결과표명，해산법재려제조성적동시능구교호지보지도상적세절문리특정、개선도상질량、제고신조비등。
For the shortcomings of the traditional filter in the noise detection and filtering, this paper presents a new noise detec-tion method and inverse harmonic mean filtering algorithm based on quotient space granular computing theory. The image with noise is divided into hierarchical granularity to form a semi order quotient space lattice, and then according to principle of falsity preserving, the proper granularity space is selected to classify the noise into two classes and it is filtered respectively. The experi-mental results show that the algorithm can filter out the noise better while keeping the details of the image texture features, im-proving image quality, and increasing signal to noise ratio.