A Novel Stereo Matching Algorithm for Digital Surface Model (DSM) Generation in Water Areas

Wenhuan Yang,Xin Li,Yu Fu,Bo Yang

doi:10.3390/rs12050870

Abstract

Image dense matching has become one of the widely used means for DSM generation due to its good performance in both accuracy and efficiency. However, for water areas, the most common ground object, accurate disparity estimation is always a challenge to excellent image dense matching methods, as represented by semi-global matching (SGM), due to the poor texture. For this reason, a great deal of manual editing is always inevitable before practical applications. The main reason for this is the lack of uniqueness of matching primitives, with fixed size and shape, used by those methods. In this paper, we propose a novel DSM generation method, namely semi-global and block matching (SGBM), to achieve accurate disparity and height estimation in water areas by adaptive block matching instead of pixel matching. First, the water blocks are extracted by seed point growth, and an adaptive block matching strategy considering geometrical deformations, called end-block matching (EBM), is adopted to achieve accurate disparity estimation. Then, the disparity of all other pixels beyond these water blocks is obtained by SGM. Last, the median value of height of all pixels within the same block is selected as the final height for this block after forward intersection. Experiments are conducted on ZiYuan-3 (ZY-3) stereo images, and the results show that DSM generated by our method in water areas has high accuracy and visual quality.

Highlights

This paper aims at solving the stereo matching problem in water areas under poor texture further, and generating reliable DSMs automatically
In contrast to the traditional dense matching methods that obtain the elevation pixel by pixel, this paper introduces a DSM generation approach semi-global and block matching (SGBM), aiming at improving the elevation estimation accuracy of water areas by adaptive block matching
This paper proposes a novel DSM generation approach called SGBM, which effectively solves the height estimation problem in poor texture areas that have almost constant height, represented by the water area

Summary

Introduction

DSM is a critical component of many physical description of the Earth’s surface, and provides the surface structures required for myriad applications as diverse as mapping, navigation, military mission and smart city. Shuttle radar topography mission (SRTM) with 30-m or 90-m resolution, has been one of the most important and widely used publicly available spatial datasets in nearly ten years [1,2]. There is a mass of data voids in SRTM, and many of them appear in water regions. Post-processes, including water detection, interpolation, and manual editing, are needed before practical applications. SRTM is no longer suitable for current various applications due to relatively low resolution. With the continuous improvement of optical remote sensing image resolution, DSM with meter and even sub-meter resolution generated by stereo matching is available [3,4,5]

Objectives

Methods

Discussion

Conclusion