期刊文献+

基于Kalman滤波与多特征模糊聚类的图像融合

Image Fusion Based on Kalman Filtering and Multi-Feature Fuzzy Clustering
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摘要 为了减低图像的噪声,保留有用的信息,获得更为可靠的融合图像,将Kalman滤波引入图像融合中,提出基于Kalman滤波与多特征模糊聚类的图像融合算法.该方法结合滤波和多特征优点,实验结果表明了该方法的有效性. To remove the noise from images while retaining the useful information and get more reliable results, The Kalman filter approach is introduced to image fusion, and a novel image fusion algorithm based on Kalman filter and multi-feature fuzzy clustering is proposed. The method combines the advantages of Kalman filter with multi-feature algorithm. The results of experiments indicate that the proposed image fusion method is effective.
出处 《江南大学学报(自然科学版)》 CAS 2007年第6期694-697,共4页 Joural of Jiangnan University (Natural Science Edition) 
基金 国家自然科学基金项目(60572034) 江苏省自然科学基金项目(BK2006081) 教育部新世纪优秀人才计划项目 图像处理与图像通信实验室开放基金项目(KJS03038) 教育部科学技术研究项目(105087)
关键词 KALMAN滤波 多尺度小波分解 图像融合 Kalman filter multi-scale wavelet decomposition image fusion
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参考文献13

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