高分二号卫星影像融合及质量评价  

Research on fusion of GF-2 imagery and quality evaluation

作　　者：孙攀[1] 董玉森[2] 陈伟涛[2] 马娇[1] 邹毅[2] 王金鹏[1] 陈华[3] 

机构地区：[1]中国地质大学(武汉)地球科学学院,武汉430074 [2]中国地质大学(武汉)计算机学院,武汉430074 [3]中国国土资源航空物探遥感中心,北京100083

出　　处：《国土资源遥感》2016年第4期108-113,共6页Remote Sensing for Land & Resources

基　　金：中国地质调查局项目"东北界河地区国土资源遥感综合调查"(编号:1212011220106);"东北边境地区基础地质遥感调查"(编号:12120115063201);国家自然科学基金项目"利用PSIn SAR监测非城市区域地面形变的关键技术研究"(编号:41001248)共同资助

摘　　要：高分二号卫星(GF-2)是我国自主研制的首颗空间分辨率优于1 m的民用光学遥感卫星,配备有0.81 m空间分辨率的全色相机和3.24 m空间分辨率的多光谱相机。对比分析适合GF-2影像的融合方法对于提高其应用效果与扩大应用领域具有实际意义。针对东北地区2014年11月22日和27日成像的GF-2影像,分别采用主成分分析(principal component analysis,PCA)、GS(Gram-Schmidt)变换、modified-HIS(intensity hue saturation)变换、高通滤波方法(high pass filter,HPF)和超球体色彩空间变换(hyperspherical color space resolution merge,HCS)等5种融合方法对多光谱和全色数据进行融合。并对5种融合影像进行质量评价,首先采用目视分析方法进行定性评价,其次采用信息熵、平均梯度、相关系数和光谱扭曲度等统计学指标进行客观定量评价,最后对融合影像进行地物分类。结果表明,HCS与GS变换融合影像无论是在视觉还是在地物分类应用上都具有较好的效果,且没有波段数的限制,最适合GF-2影像融合;HPF方法对空间细节信息的增强仅次于HCS变换,但是其光谱保真度效果最差;PCA和modified-IHS变换融合效果比较适中,可以作为GF-2影像融合的候补方法。GaoFen - 2 （ GF - 2） is the first sub - meter civilian optical remote sensing satellite of China configured with 0.81 m resolution panchromatic cameras and 3.24 m multi - spectral cameras. Researches on image fusion algorithm suitable for GF - 2 would have great significance for improving .the image quality and expanding the application scope of the satellite. Four GF - 2 images covering Northeast China from November 22 to 27, 2014 were used in this paper. The authors compared the efficiency of five fusion algorithms, which include component transform （PCA）, Gram -Schmidt （GS）, modified -HIS transform, HPF and HCS transform algorithm. In order to quantitatively assess the quality of the fused images, the authors adopted the following steps： The authors first examined the visual qualitative result and then evaluated the correlation between the original multi - spectral and the fused images. The authors compared the fused image with the original image in degree of distortion and parts of the statistical parameters such as entropy, average grads and correlation coefficient of the various frequency bands. Finally, the authors performed a supervised classification for the fused images, and compared the accuracies of resulting images. The result shows that all the fusion techniques improve the resolution and the visual effect. The HCS and GS transform algorithm could not only achieve the best results but also have no limit to the number of bands, and hence it is the most suitable method for the GF -2 image fusion. The HPF method is next only to the HCS transform method in the spatial detail enhancement, but the spectral fidelity is the worst among the five image fusion algorithms. It is moderate for the performance of the PCA and modified - IHS transform method, and then these algorithms can provide backup for the GF -2 image fusion.

关 键 词：高分二号 图像融合 质量评价 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]