摘要
研究遥感图像融合问题。针对遥感图像数据在时间、空间和光谱方面差异大,图像分辨率低等问题,为有效提高遥感图像的分辨率,提出了一种基于聚类和NSCT的遥感图像融合算法。首先对源图像进行小波变换提取源图像特征;然后利用改进的模糊C均值聚类算法在多特征形成的特征空间上对图像进行区域分割,并在此基础上对区域进行NSCT分解,通过设计的区域相似度度量方法,以信息度大的区域作为融合区域,对不同的区域采用不同的融合规则进行融合,最后进行重构得到融合图像。仿真结果表明,对比其它图像融合算法,改进的遥感图像融合算法可获得较理想的融合图像,具有一定的实用性。
In remote sensing image fusion area, the data of remote sensing images are quite different in time, space and spectrum, and the image resolutions are low. In order to improve the resolutions of remote sensing images, a fusion algorithm for remote sensing images based on improved FCM and NSCT was proposed in this paper. Firstly, tile wavelet transform was applied to source images for multi resolution decomposition and extracting the images fea- tures. Secondly, the improved fuzzy C - means clustering algorithm was used to segment the image in the feature space formed by multiple features of training samples. Then NSCT decomposition was performed on each region, through the design of the regional similarity measurement method. Taking the large content of information of region as the fusion region, we used different fusion rules on different regions. Finally, the fused image was obtained through inverse NSCT. The simulation experiment shows that the proposed algorithm is superior to other image fusion algo- rithms, feasible and effective, also can manifest better fusion effects.
出处
《计算机仿真》
CSCD
北大核心
2012年第6期278-281,共4页
Computer Simulation
基金
贵州省自然科学基金资助项目(黔教科2009064)
黔南民族师范学院科研项目(qnsy201001)
关键词
小波分析
图像融合
遥感图像
Wavelet transform
Image fusion
Remote sensing