A General Framework of Remote Sensing Epipolar Image Generation

Abstract

Epipolar images can improve the efficiency and accuracy of dense matching by restricting the search range of correspondences from 2-D to 1-D, which play an important role in 3-D reconstruction. As most of the satellite images in archives are incidental collections, which do not have rigorous stereo properties, in this paper, we propose a general framework to generate epipolar images for both in-track and cross-track stereo images. We first investigate the theoretical epipolar constraints of single-sensor and multi-sensor images and then introduce the proposed framework in detail. Considering large elevation changes in mountain areas, the publicly available digital elevation model (DEM) is applied to reduce the initial offsets of two stereo images. The left image is projected into the image coordinate system of the right image using the rational polynomial coefficients (RPCs). By dividing the raw images into several blocks, the epipolar images of each block are parallel generated through a robust feature matching method and fundamental matrix estimation, in which way, the horizontal disparity can be drastically reduced while maintaining negligible vertical disparity for epipolar blocks. Then, stereo matching using the epipolar blocks can be easily implemented and the forward intersection method is used to generate the digital surface model (DSM). Experimental results on several in-track and cross-track images, including optical-optical, SAR-SAR, and SAR-optical pairs, demonstrate the effectiveness of the proposed framework, which not only has obvious advantages in mountain areas with large elevation changes but also can generate high-quality epipolar images for flat areas. The generated epipolar images of a ZiYuan-3 pair in Songshan are further utilized to produce a high-precision DSM.

Disparity Refinement for Stereo Matching of High-Resolution Remote Sensing Images Based on GIS Data

“…This process effectively reduces the search range for matching points between image pairs from 2D to 1D, thereby significantly enhancing the accuracy and efficiency of stereo matching. However, for remote image pairs lacking a strict stereoscopic relationship, traditional epipolar constraints become inapplicable [25]. To overcome this challenge, we employ the approximate epipolar resampling method based on the local elevation surface to rectify the image pair and obtain the epipolar-rectified image pair [26].…”

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“…a study of mining operations and environmental rehabilitation processes in Vietnamese coal fields based on remote sensing data. Ugol' , 2022, (7), pp. 21-24.…”

“…На очередном этапе на шей совместной работы было принято решение о прове дении исследования угледобывающего сектора Вьетнама с использованием результатов спутниковой съемки. С по явлением технологий дистанционного зондирования Зем ли из космоса спектр прикладных исследований значи тельно расширился, о чем свидетельствуют работы рос сийских и зарубежных исследователей [1,2,3,4,5,6,7,8]. Расстояние транспортировки вскрышных пород не пре вышает 2,5 км.…”

Epipolar resampling for Satellite Linear Pushbroom Images Using Block-wise Affine Transformation Parallel Method

“…The process of epipolar resampling for satellite images differs significantly from that of conventional frame camera images. Unlike images captured by frame cameras, which can be stereo rectified with strict adherence to the epipolar geometric constraint without introducing epipolar error, images from pushbroom satellites exhibit distinct characteristics (Wang et al, 2021). Pushbroom satellites utilize the multi-central projection due to their linear array configuration (Habib et al, 2005), resulting in a deviation from a strict epipolar relationship.…”