General Structure Physics of an Aerial Remote Sensing Platform and Its Systemic Accuracy Criterion

Accuracy is a key factor in high-resolution remote sensing and photogrammetry. The factors that affect accuracy are imaging system errors and data processing errors. Due to the complexity of aerial camera errors, this paper focuses on the design of digital aerial camera systems and the means to reduce system error and data processing inefficiencies. There are many kinds of digital aerial camera systems at present;however, these systems lack a unified physical model, which ultimately leads to more complicated designs and multi-camera modes. Such a system is complex and costly, as it is easily affected by factors such as vibration and temperature. Thus, the installed accuracy can only reach the millimeter level. Here, we describe a unified physical structure for a digital aerial camera that imitates an out-of-field multi-charge-coupled device (CCD), an in-field multi-CCD, and once-imaging and twice-imaging digital camera systems. This model is referred to as the variable baseline-height ratio spatiotemporal model. The variable ratio allows the opto-mechanical spatial parameters to be linked with height accuracy, thus providing a connection to the surface elevation. The twice-imaging digital camera prototype system and the wideband limb imaging spectrometer provide a transformation prototype from the current multi-rigid once-imaging aerial camera to a single rigid structure. Thus, our research lays a theoretical foundation and prototype references for the construction and industrialization of digital aerial systems.

Fully automatic DOM generation method based on optical flow field dense image matching

Automatic Digital Orthophoto Map(DOM)generation plays an important role in many downstream works such as land use and cover detection,urban planning,and disaster assessment.Existing DOM generation methods can generate promising results but always need ground object filtered DEM generation before otho-rectification;this can consume much time and produce building facade contained results.To address this problem,a pixel-by-pixel digital differential rectification-based automatic DOM generation method is proposed in this paper.Firstly,3D point clouds with texture are generated by dense image matching based on an optical flow field for a stereo pair of images,respectively.Then,the grayscale of the digital differential rectification image is extracted directly from the point clouds element by element according to the nearest neighbor method for matched points.Subsequently,the elevation is repaired grid-by-grid using the multi-layer Locally Refined B-spline(LR-B)interpolation method with triangular mesh constraint for the point clouds void area,and the grayscale is obtained by the indirect scheme of digital differential rectification to generate the pixel-by-pixel digital differentially rectified image of a single image slice.Finally,a seamline network is automatically searched using a disparity map optimization algorithm,and DOM is smartly mosaicked.The qualitative and quantitative experimental results on three datasets were produced and evaluated,which confirmed the feasibility of the proposed method,and the DOM accuracy can reach 1 Ground Sample Distance(GSD)level.The comparison experiment with the state-of-the-art commercial softwares showed that the proposed method generated DOM has a better visual effect on building boundaries and roof completeness with comparable accuracy and computational efficiency.