Siok Katarzyna, Ewiak Ireneusz, Jenerowicz Agnieszka
Faculty of Civil Engineering and Geodesy, Military University of Technology, 00-908 Warsaw, Poland.
Sensors (Basel). 2020 Dec 11;20(24):7100. doi: 10.3390/s20247100.
The growing demand for high-quality imaging data and the current technological limitations of imaging sensors require the development of techniques that combine data from different platforms in order to obtain comprehensive products for detailed studies of the environment. To meet the needs of modern remote sensing, the authors present an innovative methodology of combining multispectral aerial and satellite imagery. The methodology is based on the simulation of a new spectral band with a high spatial resolution which, when used in the pansharpening process, yields an enhanced image with a higher spectral quality compared to the original panchromatic band. This is important because spectral quality determines the further processing of the image, including segmentation and classification. The article presents a methodology of simulating new high-spatial-resolution images taking into account the spectral characteristics of the photographed types of land cover. The article focuses on natural objects such as forests, meadows, or bare soils. Aerial panchromatic and multispectral images acquired with a digital mapping camera (DMC) II 230 and satellite multispectral images acquired with the S2A sensor of the Sentinel-2 satellite were used in the study. Cloudless data with a minimal time shift were obtained. Spectral quality analysis of the generated enhanced images was performed using a method known as "consistency" or "Wald's protocol first property". The resulting spectral quality values clearly indicate less spectral distortion of the images enhanced by the new methodology compared to using a traditional approach to the pansharpening process.
对高质量成像数据不断增长的需求以及成像传感器当前的技术限制，要求开发能够整合来自不同平台数据的技术，以便获得用于详细环境研究的综合产品。为满足现代遥感的需求，作者提出了一种结合多光谱航空影像和卫星影像的创新方法。该方法基于对具有高空间分辨率的新光谱带的模拟，在全色锐化过程中使用时，与原始全色波段相比，可产生具有更高光谱质量的增强图像。这很重要，因为光谱质量决定了图像的进一步处理，包括分割和分类。本文提出了一种考虑所拍摄土地覆盖类型光谱特征来模拟新的高空间分辨率图像的方法。本文重点关注森林、草地或裸土等自然物体。研究中使用了用数字测绘相机（DMC）II 230获取的航空全色和多光谱图像以及用哨兵 - 2卫星的S2A传感器获取的卫星多光谱图像。获取了时间偏移最小的无云数据。使用一种称为“一致性”或“沃尔德协议首要属性”的方法对生成的增强图像进行光谱质量分析。结果光谱质量值清楚地表明，与使用传统全色锐化方法相比，新方法增强的图像光谱失真更小。
