Stereo rectification of pushbroom satellite images by robustly estimating the fundamental matrix

Tatar, Nurollah; Arefi, Hossein

doi:10.1080/01431161.2019.1624862

Cited by 13 publications

(8 citation statements)

References 30 publications

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“…The results of the epipolar resampling are shown in Table III. We list the results of the method proposed by Tatar et al [36] for comparison. parallax of all the corresponding points in an image pair.…”

Section: B Resultsmentioning

confidence: 99%

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

Yi¹,

Chen

Wang

et al. 2021

IEEE Access

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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*3000 pixels, significantly less than the similar method.INDEX TERMS Epipolar resampling; multi-view; push-broom satellite image; block size; fundamental matrix.

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Section: B Resultsmentioning

confidence: 99%

“…The results show that the errors of these two methods are similar. In 2019, Tatar et al [36] developed an epipolar resampling method by robustly estimating the fundamental matrix. They estimated fundamental matrix using two geometric constraints.…”

Section: Related Workmentioning

confidence: 99%

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

Yi¹,

Chen

Wang

et al. 2021

IEEE Access

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“…In the pre-processing step, the stereo images are resampled along the epipolar geometry. Due to the small size of the selected stereo image tiles, the epipolar images are generated using a fundamental matrix (Tatar and Arefi, 2019). The evaluation of epipolar resampling show that the epipolar images are generated with sub-pixel accuracy.…”

Section: Resultsmentioning

confidence: 99%

“…Unlike the images with perspective geometry, the epipolar geometry of satellite stereo images could not be considered as a straight line. Recently, for linear consideration of epipolar geometry in satellite stereo images, an image tiling strategy has been proposed to produce epipolar images from high resolution satellite stereo image (de Franchis et al, 2014;Tatar and Arefi, 2019). In this paper, the high resolution satellite stereo images are also rectified based on these approaches.…”

Section: Cost Aggregation Methodsmentioning

confidence: 99%

Evaluation of Selected Cost Aggregation Methods on High Resolution Satellite Stereo Images

Tatar

Arefi

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Dense stereo processing requires a critical step that called cost aggregation or cost optimization. Most of the cost aggregation methods are evaluated on close range stereo images from Middlebury or KITTI datasets. While the effect of cost aggregation on high resolution satellite stereo processing has not yet been sufficiently evaluated. In this paper, three typical cost aggregation methods together with another approach which is a combination of these methods are evaluated on high resolution satellite stereo images and then are compared with LiDAR ground truth. These methods including Semi-Global Matching (SGM), Guided Filtering (GF), iterative GF (IGF), and SGM followed by GF (SGM-GF) with Census and Zero Normalized Cross Correlation (ZNCC) cost functions. Although the Census cost function has a good performance on the border of the objects and low blurring effects, the results of both cost functions, i.e. Census and ZNCC, have same treatment on all stereo methods. Also, in order to make an impartial assessment, for all stereo methods, we do not perform any disparity map refinement. The bad-pixel criteria with an absolute difference height error greater than 2 meters for SGM, GF, IGF, and SGM-GF methods is 36.7%, 34.8%, 33.8%, and 28.6% respectively. Also, the Normalized Median Absolute Difference (NMAD) error for SGM, GF, IGF, and SGM-GF is 1.29, 1.15, 1.06, and 0.94 meters, respectively. Overall, the experimental results on WV III stereo images demonstrate that the SGM method has lower accuracy and SGM-GF method is accurate than other methods.

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“…According to the research of Kim et al [13], although the epipolar lines in pushbroom images are hyperbolic curves, the epipolar lines can be approximately treated as straight lines in small local areas. Using this property, Woo et al [32] and Tatar et al [33] achieved the epipolar resampling of pushbroom satellite images by dividing the large images into small tiles. However, how to choose the size of the image tile is a problem that needs to be further studied.…”

Section: B Evaluation Metricsmentioning

confidence: 99%

Methods for the Epipolarity Analysis of Pushbroom Satellite Images Based on the Rational Function Model

Chen

Wang

et al. 2020

IEEE Access

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Epipolarity is the foundation of epipolar resampling, which is used to eliminate the vertical disparity between stereo pairs in stereo matching. To analyze the epipolarity of pushbroom satellite images, this paper compares three methods based on the rational function model (RFM): the projection trajectory method (PTM), the piecewise projection trajectory method (PPTM) and our extended projection trajectory method (EPTM). To evaluate the quality of epipolar curves, we defined the deviation coefficient as a metric to evaluate the bending degree of epipolar curves. We also defined the maximum deviation coefficient of an image that can be used to determinate the tile size in multiview satellite image 3D reconstruction based on image dividing. Comparison experiments have been carried out with pushbroom satellite images using these three methods. Experimental results show that our EPTM is more convenient and practical. It only needs the forward form of the RFM to analyze the epipolarity and can be used in the epipolarity analysis of a single image. By projecting straight lines in the ground space into the image space, the EPTM can be used to perform comprehensive epipolarity analysis for pushbroom satellite images. In addition, the EPTM can be used to calculate the maximum deviation coefficient of an image that the PTM and the PPTM cannot calculate, which is important in 3D reconstruction using multiview satellite images. INDEX TERMS Epipolarity; stereo matching; pushbroom satellite image; RFM; projection trajectory method; deviation coefficient.

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Stereo rectification of pushbroom satellite images by robustly estimating the fundamental matrix

Cited by 13 publications

References 30 publications

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

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

Evaluation of Selected Cost Aggregation Methods on High Resolution Satellite Stereo Images

Methods for the Epipolarity Analysis of Pushbroom Satellite Images Based on the Rational Function Model

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