Epipolar Resampling of Cross-Track Pushbroom Satellite Imagery Using the Rigorous Sensor Model

Jannati, Mojtaba; Zoej, Mohammad Javad Valadan; Mokhtarzade, Mehdi

doi:10.3390/s17010129

Cited by 13 publications

(11 citation statements)

References 21 publications

(42 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In recent years, some works have directly used the pre-corrected RFM as the projection model, without making any simplification when modeling the epipolar relationship. In other works [24,25], the authors used 2D polynomial functions calculated with conjugate image points to transform the epipolar curves into straight lines. In another paper [26], the authors used block-wise transformation to transform the epipolar curves into straight lines.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

An SRTM-Aided Epipolar Resampling Method for Multi-Source High-Resolution Satellite Stereo Observation

Xia

2019

Remote Sensing

View full text Add to dashboard Cite

Binocular stereo observation with multi-source satellite images used to be challenging and impractical, but is now a valuable research issue with the introduction of powerful deep-learning-based stereo matching approaches. However, epipolar resampling, which is critical for binocular stereo observation, has rarely been studied with multi-source satellite images. The main problem is that, under the multi-source stereo mode, the epipolar-line-direction (ELD) at an image location may vary when computed with different elevations. Thus, a novel SRTM (Shuttle Radar Topography Mission)-aided approach is proposed, where a point is transformed from the original image-space to the epipolar image-space through a global rotation, followed by a block-wise homography transformation. The global rotation transfers the ELDs at the center of the overlapping area to the x-axis, and then block-wise transformation shifts the ELDs of all grid-points to the x-axis and eliminates the y-disparities between the virtual corresponding points. Experiments with both single-source and multi-source stereo images showed that the proposed method is obviously more accurate than the previous methods that do not use SRTM. Moreover, with some of the multi-source image pairs, only the proposed method ensured the y-disparities remained within ±1 pixel.

show abstract

Section: Related Workmentioning

confidence: 99%

“…Before obtaining the ELDs, we need to find the corresponding points. Some approaches [24,25] directly use the matched tie-points. However, this may not be a good choice for production since the resampling accuracy will be influenced by the matching error and the spatial distribution of the tie-points.…”

Section: Obtaining Epipolar-line-directionsmentioning

confidence: 99%

An SRTM-Aided Epipolar Resampling Method for Multi-Source High-Resolution Satellite Stereo Observation

Xia

2019

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Despite the popularity and multiple achievements of terrain independent RFMs and their widespread use for high resolution satellite images, the terrain dependent RFMs were not really welcomed [8][9][10]. At least, this can be due to two main reasons: (1) Third-order 3D RFMs encompass 80 parameters [11], none of which are totally independent [12,13].…”

Section: Introductionmentioning

confidence: 99%

A Knowledge-Based Search Strategy for Optimally Structuring the Terrain Dependent Rational Function Models

2017

Self Cite

View full text Add to dashboard Cite

Abstract:Identifying the optimal structure of terrain dependent Rational Function Models (RFMs) not only decreases the number of Ground Control Points (GCPs) required, but also increases the accuracy of the model, by reducing the multi-collinearity of Rational Polynomials Coefficients (RPCs) and avoiding the ill-posed problem. Global optimization algorithms such as Genetic Algorithm (GA), evaluate the different combinations of parameters effectively. Therefore, they have a high ability to detect the optimal structure of RFMs. However, one drawback of these algorithms is their high computation cost. This article proposes a knowledge-based search strategy to overcome this deficiency. The backbone of the proposed method relies on the technical knowledge about the geometric condition of image at the time of acquisition, as well as the effect of external factors such as terrain relief on the image. This method was evaluated on four different datasets, including a SPOT-1A, a SPOT-1B, an IKONOS-Geo image, and a GeoEye-Geo imagery, using various number of GCPs. Experimental results demonstrate the efficiency of the proposed method to achieve a sub-pixel accuracy using few GCPs (only 4-6 points) in all datasets. The results also indicate that the proposed method improves the computation speed by 140 times when comparing with GA.

show abstract

“…Sensor model of HRSI is crucial to land and ocean mapping, which is typically divided into two categories, namely the rigorous sensor models (RSMs) and generalized models (GL) (Poli and Toutin, 2012). The RSMs of space-borne linear array chargecoupled device (CCD) optical imagery is mainly based on linear array co-linearity equation according with interior orientation (IO) and exterior orientation (EO) parameters of imagery (Poli 2015;Jannati et al, 2017). However, each satellite sensor has its own imaging system with various RSMs which increase the difficulty of developing geometric processing software that is capable of handling multi-source remote sensing data.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the RPC Model for Ziyuan-3 Three-Line Array Imagery

Hong¹,

Xu²,

Zhang³

et al. 2017

Preprint

View full text Add to dashboard Cite

Ziyuan-3 (ZY-3) satellite is the first civilian stereo mapping satellite in China and was designed to achieve the 1: 50000 scale mapping for land and ocean. Rigorous sensor model (RSM) is required to build the relationship between the three-dimensional (3D) object space and two-dimensional (2D) image space of ZY-3 satellite imagery. However, each satellite sensor has its own imaging system with different physical sensor models, which increase the difficulty of geometric integration of multi-source images with different sensor models. Therefore, it is critical to generate generic model especially rational polynomial coefficients (RPCs) of optical imagery. Recently, relatively a few researches have been conducted on RPCs generation to ZY-3 satellite. This paper proposes an approach to evaluate the performance of RPCs generation from RSM of ZY-3 imagery. Three scenarios experiments with different terrain features (such as ocean, city and grassland) are designed and conducted to comprehensively evaluate the replacement accuracies of this approach and analyze the RPCs fitting error. All the experimental results demonstrate that the proposed method achieved encouraging accuracy of better than 1.946E-04 pixel in both x-axis direction and y-axis direction, it indicates that the RPCs is suitable for ZY-3 imagery and can be used as a replacement for the RSM of ZY-3 imagery.

show abstract

Epipolar Resampling of Cross-Track Pushbroom Satellite Imagery Using the Rigorous Sensor Model

Cited by 13 publications

References 21 publications

An SRTM-Aided Epipolar Resampling Method for Multi-Source High-Resolution Satellite Stereo Observation

An SRTM-Aided Epipolar Resampling Method for Multi-Source High-Resolution Satellite Stereo Observation

A Knowledge-Based Search Strategy for Optimally Structuring the Terrain Dependent Rational Function Models

Evaluation of the RPC Model for Ziyuan-3 Three-Line Array Imagery

Contact Info

Product

Resources

About