LBV变换在国产ZY-3卫星影像中应用研究探讨  

Research on the application of LBV transformation in domestic ZY-3 satellite images

作　　者：卫宝泉 索安宁[2] 李颖[1] 赵建华[2] WEI Baoquan;SUO Anning;LI Ying;ZHAO Jianhua(College of Navigation, Dalian Maritime University, Dalian 116026, China;NationalMarine Environmental Monitoring Center, Dalian 116023, China)

机构地区：[1]大连海事大学航海学院,大连116026 [2]国家海洋环境监测中心,大连116023

出　　处：《国土资源遥感》2019年第3期87-94,共8页Remote Sensing for Land & Resources

基　　金：国家自然科学基金面上项目“海上搜寻目标光谱探测追踪研究”(编号:41571336)和国家自然科学基金项目“基于激光荧光的冰区船舶溢油识别研究”(编号:51609032)共同资助

摘　　要：根据国产资源三号(ZY-3)卫星遥感影像光谱特征,提出并推导适用于ZY-3遥感影像的LBV变换公式,探讨该方法在提高国产ZY-3卫星影像质量的可行性。首先,针对ZY-3遥感影像特点,选择9类典型地物光谱信息,通过回归分析求解回归系数;然后,根据影像典型地物空间(裸地、水体、植被)、色彩空间(红、绿、蓝)及LBV变量空间(地物总体辐射水平、可见光—近红外辐射平衡、辐射变换矢量)之间特点计算推导ZY-3卫星影像的L,B,V这3个分量;最后,利用福建省宁德市ZY-3遥感影像进行实验,定量分析评价实验结果。结果表明:①从目视效果看,相比原始影像,变换后影像更加清晰,层次感更强,细节信息也更为丰富,从而更有利于后续地物的判定、识别;②该方法得到的影像信息熵为6.21,平均梯度为4.71,偏差系数为0.46,变换后遥感影像质量较好;③该方法对ZY-3遥感影像分类的总体精度最高达89.71%,Kappa系数最高为0.875 3,分类精度较高。因此,该方法能很好地提高ZY-3遥感影像质量,可用于ZY-3遥感影像处理及后续信息提取工作。According to the spectral features of domestic ZY-3 remote sensing images, the formula of LBV transformation for ZY-3 is proposed and deduced, and the feasibility of improving the quality of ZY-3 remote sensing images is testified. At first, based on the characteristics of ZY-3 remote sensing images, the spectral information of nine types of typical ground features were selected, and regression coefficients were used to calculate regression coefficients. Then, the three components of L, B, V of ZY-3 satellite images were calculated according to the characteristics of the typical ground features space (bare land, water body, vegetation), color space (red, green, blue) and the space of LBV variables (the general radiance level of the ground objects, the visiable - infrared radiation balance, the band radiance variation vector). Finally, the experiments of ZY-3 remote sensing image in Ningde City of Fujian Province were carried out, and quantitative analysis was conducted to evaluate the experimental results. Firstly, the results show that, in the aspect of the visual effects, compared with the original image, the transformed image is more clear, and the details are more abundant, and thus can contribute more to the determination and identification of subsequent features. Secondly, through the LBV transformation, the image information entropy is 6.21, the average gradient is 4.71, the deviation coefficient is 0.46, and the quality of the remote sensing image is better than other transformation methods. Thirdly, by classifying the LBV image, the overall accuracy is up to 89.71%, and the Kappa coefficient is the highest, reaching 0.875 3. The classification accuracy is higher than that of other transformation methods. Therefore, The LBV transformation can improve the quality of ZY-3 remote sensing image, and it can be applied to ZY-3 remote sensing image processing and information extraction.

关 键 词：LBV变换 图像变换 高空间分辨率 ZY-3卫星 精度分析 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]