Exploiting the Redundancy of Multiple Overlapping Aerial Images for Dense Image Matching Based Digital Surface Model Generation

Abstract

Abstract:In recent years, significant development in the domain of dense image matching (DIM) can be observed. Meanwhile, in most countries, aerial images are acquired countrywide on a regular basis with decreasing time intervals and increasing image overlaps. Therefore, aerial images represent a growing potential for digital surface model (DSM) acquisition and updating. Surface reconstruction by image matching, in most cases, requires dealing with the redundancy caused by multiple overlapping images. Many approaches considering this redundancy in the surface reconstruction process have been developed. However, there is no commonly accepted procedure for this task. From the experience of the author, it can be stated that currently applied methods show some limitations regarding DSM generation from aerial images. Therefore, it is claimed that there is room for the development of new algorithms for integration of dense image matching results from multiple stereo pairs. Methods dedicated to aerial image based DSM generation that would exploit the specificity of this task are desirable. In this paper, an approach to compute the DSM elevations from redundant elevation hypotheses derived by pairwise dense image matching is presented. The proposed approach takes into account the base-to-height (b/h) ratio of stereo pairs, the distribution of elevation hypotheses from multiple stereo pairs and the neighboring elevations. An algorithm of selection of the elevation hypotheses used for the calculation of the final DSM elevation for each grid cell was developed. The algorithm was used to generate the DSM based on two sets of aerial images having significantly different acquisition parameters. The results were compared to the models obtained from several commonly used software packages for image based DSM generation. The quality assessment was carried out by visual inspection of terrain profiles and shaded surface display as well as by the planarity control of flat parts of the terrain. The assessment of the results showed that the application of the proposed algorithm can bring some advantages and it can contribute to improving the quality of the DSM.

Using Canopy Height Model Obtained with Dense Image Matching of Archival Photogrammetric Datasets in Area Analysis of Secondary Succession

“…Such a statement is also true for LiDAR-based DSM resolution [45]. Interpolation in DSM generation can also have an impact on model quality [28].…”

“…The most promising technique in recent years-semi-global matching (SGM) [20][21][22][23][24]-has enabled obtaining xyz point clouds, characterized by high position accuracy, based on photogrammetric images [25,26]. These two algorithms are often compared [27,28]. An attempt at description of the state-of-art in image matching and the efficiency of DSM generation, with the use of different algorithms in commercial software packages, was carried out by EuroSDR [29].…”

Capela da Fazenda Veneza: análise comparativa da precisão de nuvens de pontos obtidas por diferentes ferramentas e técnicas de fotogrametria

“…Ponderando essas questões, é primordial observar a confiabilidade de uma aplicação de fototriangulação, que deve ser definida pelo seu grau de precisão e nível de detalhe, especialmente a nitidez das arestas dos objetos (DOMINIK, 2017).…”

Reliable and Efficient UAV Image Matching via Geometric Constraints Structured by Delaunay Triangulation

“…On the one hand, image pyramids should be constructed to achieve the scale-invariant property, such as the LBD and VLD line descriptors; on the other hand, SIFT-like descriptors are computed for all line strips that form the neighboring structure of one corresponding point. For UAV images with high resolutions, these two steps would cause extremely high time costs compared with other steps in the pipeline of local feature-based matching [32].…”