English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

As the basis of stereo observation, epipolar resampling is a critical technology for 3D reconstruction. With the development of the 3D reconstruction using multi-view satellite images, the epipolar resampling of the multi-view satellite images has become a new challenging problem. In this paper, we propose an epipolar resampling method for multi-view high resolution satellite images based on block. Firstly, we establish the relationship between the vertical parallax and image block size for the epipolar resampling based on block. Using this relationship, we can choose the block size to limit the maximum vertical parallax in epipolar resampling. Secondly, we use the rational function model (RFM) to generate virtual corresponding points for fundamental matrix estimation, so image pairs with large stereo angles and poor consistency in multi-view satellite images which are difficult to extract feature matching point can be rectified. Experiments with multi-view satellite images demonstrated the universality and effectiveness of the proposed method. All the image pairs in the multi-view satellite image dataset were rectified successfully. The average epipolar resampling error is only 0.25 pixels when we rectify the multi-view satellite images acquired by WorldView-3 with the block size of 3000&#x002A;3000 pixels, significantly less than the similar method.

An Epipolar Resampling Method for Multi-View High Resolution Satellite Images Based on Block