Investigation of Image Fusion Between High—Resolution Image and Multi—Spectral Image

On the basis of a thorough understanding of the physical characteristics of remote sensing image,this paper employs the theories of wavelet transform and signal sampling to develop a new image fusion algorithm.The algorithm has been successfully applied to the image fusion of SPOT PAN and TM of Guangdong province, China The experimental results show that a perfect image fusion can be built up by using the image analytical solution and reconstruction in the image frequency domain based on the physical characteristics of the image formation.The method has demonstrated that the results of the image fusion do not change spectral characteristics of the original image.     

Bayesian and Geostatistical Approaches to Combining Categorical Data Derived from Visual and Digital Processing of Remotely Sensed Images

This paper seeks a synthesis of Bayesian and geostatistical approaches to combining categorical data in the context of remote sensing classification. By experiment with aerial photographs and Landsat TM data, accuracy of spectral, spatial, and combined classification results was evaluated. It was confirmed that the incorporation of spatial information in spectral classification increases accuracy significantly. Secondly, through test with a 5-class and a 3-class classification schemes, it was revealed that setting a proper semantic framework for classification is fundamental to any endeavors of categorical mapping and the most important factor affecting accuracy. Lastly, this paper promotes non-parametric methods for both definition of class membership profiling based on band-specific histograms of image intensities and derivation of spatial probability via indicator kriging, a non-parametric geostatistical technique.     

Comparison between four methods for data fusion of ETM+ multispectral and pan images

Four data fusion methods, principle component transform (PCT), brovey transform (BT), smoothing filter-based intensity modulation (SFIM), and hue, saturation, intensity (HSI), are used to merge Landsat—7 ETM+ multispectral bands with ETM+ panchromatic band. Each of them improves the spatial resolution effectively but distorts the original spectral signatures to some extent. SFIM model can produce optimal fusion data with respect to preservation of spectral integrity. However, it results the most blurred and noisy image if the coregistration between the multispectral and pan images is not accurate enough. The spectral integrity for all methods is preserved better if the original multispectral images are within the spectral range of ETM+ pan image.     

Fusion of TerraSAR-x and Landsat ETM+ data for protected area mapping in Uganda

TerraSAR-X satellite acquires very high spatial resolution data with potential for detailed land cover mapping. A known problem with synthetic aperture radar (SAR) data is the lack of spectral information. Fusion of SAR and multispectral data provides opportunities for better image interpretation and information extraction. The aim of this study was to investigate the fusion between TerraSAR-X and Landsat ETM+ for protected area mapping using high pass filtering (HPF), principal component analysis with band substitution (PCA) and principal component with wavelet transform (WPCA). A total of thirteen land cover classes were identified for classification using a non-parametric C 4.5 decision tree classifier. Overall classification accuracies of 74.99%, 83.12% and 85.38% and kappa indices of 0.7220, 0.8100 and 0.8369 were obtained for HPF, PCA and WPCA fusion approaches respectively. These results indicate a high potential for a combined use of TerraSAR-X and Landsat ETM+ data for protected area mapping in Uganda.     

高分五号高光谱数据融合方法比较

数据融合是解决高光谱卫星在时空分辨率等指标上受限的有效途径,探讨不同方法在GF-5高光谱数据上的融合效果,对GF-5高光谱数据的信息挖掘与推广应用有着重要意义。本文本着算法简单易用、适于推广的原则,采用GS（Gram-Schmidt）葛兰—施密特正交变换融合算法、GSA（GS Adaptive）自适应GS融合算法、CNMF（Coupled Non-negative Matrix Factorization）耦合非负矩阵分解融合算法、CRISP-W（Color Resolution Improvement Software Package with Wavelet transform）基于小波变换和CRISP-B（Color Resolution Improvement Software Package with Butterworth）基于巴特沃斯滤波器的分辨率提升融合算法、GLP（Generalized Laplacian Pyramid）广义拉普拉斯金字塔融合算法共6种融合方法,分别对BJ-2、GF-2、GF-1、GF-1C、GF-1D国产卫星多光谱数据与GF-5高光谱数据进行融合实验。通过目视分析、指标评价（相关系数、通用图像质量指标、峰值信噪比、光谱角、全局综合误差）、分类应用、时间成本4种方式对融合结果进行综合比较分析。结果表明,相融合的一组图像系列相同、空间分辨率相差越小,融合结果越好。CRISP-B、CRISP-W、GLP在提升空间分辨率、光谱保真度方面能达到较好的平衡,空间重建方面,GLP稍优且更稳定,CRISP-B、CRISP-W则在光谱信息保持方面稳定性更强且效果更好。数据源会对融合方法产生一定的影响,在光谱特征信息提取、分析等对光谱保真度要求高的工作中,GLP更适合同源数据（如GF-5与GF-1/1C/1D/2）融合,而在多源数据间（如GF-5与BJ-2）进行融合时,则优先选择CRISP-W。CNMF存在一定程度的色彩畸变,且运行时间较长。GSA、GS融合效果最差,其中,GSA不论是光谱保持能力还是空间分辨率提升能力均较GS更稳定。在小样本高光谱图像分类应用中,CRISP-B融合结果分类效果稳定,分类精度较高。GSA融合结果空间细节丰富,虽光谱失真较为严重,但同时增大了地物光谱分离度,仍适用于准确勾勒建筑物、道路等地物。本研究为GF-5高光谱数据与其他国产卫星多光谱数据融合方法的选择提供参考,有助于高分五号高光谱数据的应用与推广。     

ASTER和TM/ETM+遥感数据融合监测土地覆盖变化

在人们纷纷选择IKONOS、QUICKBIRD、SPOT-5等高分辨率影像监测土地利用/覆盖变化之际,以北京海淀区为例,尝试采用Brovey变换和主成分分析(PCA)法融合ASTER、TM/ETM+中等分辨率影像,充分利用ASTER、TM/ETM+数据的多光谱和较高空间分辨率特性,挖掘其在土地覆盖变化监测中的潜力,为大规模监测土地利用/覆盖变化提供科学参考。研究将2003年ASTER多光谱3N、2、1波段与1999年ETM+PAN波段进行Brovey变换;1992年TM543与1999年ETM+PAN波段进行PCA融合,快速发现土地覆盖变化信息。经验证,变化发现精度达92.50%,符合项目精度要求。试验表明:在缺乏高分辨率影像的地区,选择价格相对便宜的AS-TER和TM/ETM+数据,采用Brovey变换和主成分分析(PCA)法进行融合,可有效监测土地覆盖变化,节约动态监测成本,二者具有很大的应用价值,值得推广。     

Use of ETM+ images to extend stem volume estimates obtained from LiDAR data

Airborne LiDAR techniques can provide accurate measurements of tree height, from which estimates of stem volume and forest woody biomass can be obtained. These techniques, however, are still expensive to apply repeatedly over large areas. The current paper presents a methodology which first transforms mean stand heights obtained from LiDAR over small strips into relevant stem volume estimates. These are then extended over an entire forest by applying two estimation methods (k-NN and locally calibrated regression) to Landsat ETM+ images. The methodology is tested over a coastal area covered by pine forest in the Regional Park of San Rossore (Central Italy). The results are evaluated by comparison with the ground stem volumes of a recent forest inventory, taking into consideration the effect of stand size. In general, the accuracies of two estimation methods are dependent on the size of the forest stands and are satisfactory only when considering stands larger than 5-10 ha. The outputs of the parametric regression procedure are slightly more stable than those of k-NN and more faithfully reproduce the spatial patterns of the ground data.     

一种快速的全色和多光谱图像融合算法

针对非下采样Contourlet变换(NSCT)在全色和多光谱图像融合中计算复杂度较高的问题,文章提出了一种快速的基于NSCT和超维彩色空间变换(HCT)相结合的融合算法:采用HCT变换提取多光谱图像的亮度分量,使得任意波段的多光谱图像跟全色图像融合的计算复杂度降低;采用NSCT进行融合,使得融合结果的空间分辨率提高的同时,保留原光谱特性。基于Pleiades卫星图像的实验结果表明,跟NSCT变换相比,本文提出的融合算法的融合结果空间细节更加突出,光谱畸变更小,同时计算复杂度显著降低。     

GF-2和Sentinel-2全色多光谱影像融合方法比较研究

针对高分二号(GF-2)卫星全色遥感影像与哨兵二号(Sentinel-2)卫星多光谱遥感影像空间分辨率相差较大且传感器不同导致的光谱或空间信息丢失问题,结合快速离散Curvelet变换对HSV融合方法的分量替换过程进行改进,利用GF-2的高空间分辨率和Sentinel-2的多光谱特性分别设计高、低频系数融合规则,并且与...     

顾及光谱特性的多光谱与全色影像HIS融合方法

应用CHIS(Generalized-Hue-Intensity-Saturation)变换融合多光谱影像与全色影像中存在的光谱扭曲问题,主要是由于变换后的I分量与全色影像之间差异过大.为此,本文提出了一种基于统计关系定权的I分量计算方法,从数据整体角度考虑,在不能获取I分量与多光谱影像准确函数关系情况下,通过各波段影...     

Spatial database updating using active contours for multispectral images: application with Landsat 7

This paper presents a fully automated approach for area detection and delineation based on multispectral images and features from a topographic database. The vectors residing in the database are refined using active contours (snakes) according to updated information provided by the multispectral images. The conventional methods of defining the external energy guiding the deformation of the snake based on: (1) statistical measures; or (2) gradient-based boundary finding is often corrupted by poor image quality. Here a method to integrate the two approaches is proposed using an estimation of the maximum a posteriori (MAP) segmentation in an effort to form a unified approach that is robust to noise and poor edges. We further propose to improve the accuracy of the resulting boundary location and update of the snake topology. A number of experiments are performed on both synthetic and LANDSAT 7 images to evaluate the approach.     

遥感影像的融合--SPOT全色波段和多光谱影像的融合

按照影像融合的一般理论,结合Erdas软件功能实现了SPOT全色波段和多光谱影像的融合。