A MATCHING METHOD TO REDUCE THE INFLUENCE OF SAR GEOMETRIC DEFORMATION

There are large geometrical deformations in SAR image, including foreshortening, layover, shade，which leads to SAR Image matching with low accuracy. Especially in complex terrain area, the control points are difficult to obtain, and the matching is difficult to achieve. Considering the impact of geometric distortions in SAR image pairs, a matching algorithm with a combination of speeded up robust features (SURF) and summed of normalize cross correlation (SNCC) was proposed, which can avoid the influence of SAR geometric deformation. Firstly, SURF algorithm was utilized to predict the search area. Then the matching point pairs was selected based on summed of normalized cross correlation. Finally, false match points were eliminated by the bidirectional consistency. SURF algorithm can control the range of matching points, and the matching points extracted from the deformation area are eliminated, and the matching points with stable and even distribution are obtained. The experimental results demonstrated that the proposed algorithm had high precision, and can effectively avoid the effect of geometric distortion on SAR image matching. Meet accuracy requirements of the block adjustment with sparse control points.

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Feature Matching Combining Radiometric and Geometric Characteristics of Images, Applied to Oblique- and Nadir-Looking Visible and TIR Sensors of UAV Imagery

Sensors ◽

10.3390/s21134587 ◽

2021 ◽

Vol 21 (13) ◽

pp. 4587

Author(s):

Hyoseon Jang ◽

Sangkyun Kim ◽

Suhong Yoo ◽

Soohee Han ◽

Hong-Gyoo Sohn

Keyword(s):

Image Matching ◽

Information Needs ◽

Feature Matching ◽

Phase Congruency ◽

Scale Invariant ◽

Surface Information ◽

Speeded Up Robust Features ◽

Image Pairs ◽

3D Information ◽

Matching Techniques

A large amount of information needs to be identified and produced during the process of promoting projects of interest. Thermal infrared (TIR) images are extensively used because they can provide information that cannot be extracted from visible images. In particular, TIR oblique images facilitate the acquisition of information of a building’s facade that is challenging to obtain from a nadir image. When a TIR oblique image and the 3D information acquired from conventional visible nadir imagery are combined, a great synergy for identifying surface information can be created. However, it is an onerous task to match common points in the images. In this study, a robust matching method of image pairs combined with different wavelengths and geometries (i.e., visible nadir-looking vs. TIR oblique, and visible oblique vs. TIR nadir-looking) is proposed. Three main processes of phase congruency, histogram matching, and Image Matching by Affine Simulation (IMAS) were adjusted to accommodate the radiometric and geometric differences of matched image pairs. The method was applied to Unmanned Aerial Vehicle (UAV) images of building and non-building areas. The results were compared with frequently used matching techniques, such as scale-invariant feature transform (SIFT), speeded-up robust features (SURF), synthetic aperture radar–SIFT (SAR–SIFT), and Affine SIFT (ASIFT). The method outperforms other matching methods in root mean square error (RMSE) and matching performance (matched and not matched). The proposed method is believed to be a reliable solution for pinpointing surface information through image matching with different geometries obtained via TIR and visible sensors.

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A SAR Image Matching Algorithm Based on Target Detection

JOURNAL OF ELECTRONICS INFORMATION TECHNOLOGY ◽

10.3724/sp.j.1146.2007.00920 ◽

2011 ◽

Vol 30 (12) ◽

pp. 2818-2821 ◽

Cited By ~ 1

Author(s):

Hui Zhang ◽

Jian-guo Wang

Keyword(s):

Target Detection ◽

Image Matching ◽

Sar Image ◽

Matching Algorithm

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Research on Remote Sensing Image Matching with Special Texture Background

Symmetry ◽

10.3390/sym13081380 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1380

Author(s):

Sen Wang ◽

Xiaoming Sun ◽

Pengfei Liu ◽

Kaige Xu ◽

Weifeng Zhang ◽

...

Keyword(s):

Remote Sensing ◽

Remote Sensing Image ◽

Geometric Distortion ◽

Reference Image ◽

Remote Sensing Images ◽

Scale Invariant ◽

Sift Algorithm ◽

Speeded Up Robust Features ◽

Adaptive Quantization ◽

Texture Background

The purpose of image registration is to find the symmetry between the reference image and the image to be registered. In order to improve the registration effect of unmanned aerial vehicle (UAV) remote sensing imagery with a special texture background, this paper proposes an improved scale-invariant feature transform (SIFT) algorithm by combining image color and exposure information based on adaptive quantization strategy (AQCE-SIFT). By using the color and exposure information of the image, this method can enhance the contrast between the textures of the image with a special texture background, which allows easier feature extraction. The algorithm descriptor was constructed through an adaptive quantization strategy, so that remote sensing images with large geometric distortion or affine changes have a higher correct matching rate during registration. The experimental results showed that the AQCE-SIFT algorithm proposed in this paper was more reasonable in the distribution of the extracted feature points compared with the traditional SIFT algorithm. In the case of 0 degree, 30 degree, and 60 degree image geometric distortion, when the remote sensing image had a texture scarcity region, the number of matching points increased by 21.3%, 45.5%, and 28.6%, respectively and the correct matching rate increased by 0%, 6.0%, and 52.4%, respectively. When the remote sensing image had a large number of similar repetitive regions of texture, the number of matching points increased by 30.4%, 30.9%, and −11.1%, respectively and the correct matching rate increased by 1.2%, 0.8%, and 20.8% respectively. When processing remote sensing images with special texture backgrounds, the AQCE-SIFT algorithm also has more advantages than the existing common algorithms such as color SIFT (CSIFT), gradient location and orientation histogram (GLOH), and speeded-up robust features (SURF) in searching for the symmetry of features between images.

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Explore Better Network Framework for High Resolution Optical and SAR Image Matching

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2021.3126939 ◽

2021 ◽

pp. 1-1

Author(s):

Han Zhang ◽

Lin Lei ◽

Weiping Ni ◽

Tao Tang ◽

Junzheng Wu ◽

...

Keyword(s):

High Resolution ◽

Image Matching ◽

Sar Image

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Modifications in the SIFT operator for effective SAR image matching

International Journal of Image and Data Fusion ◽

10.1080/19479832.2010.495322 ◽

2010 ◽

Vol 1 (3) ◽

pp. 243-256 ◽

Cited By ~ 52

Author(s):

Sahil Suri ◽

Peter Schwind ◽

Johannes Uhl ◽

Peter Reinartz

Keyword(s):

Image Matching ◽

Sar Image

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On the feasibility of selective spatial correlation to accelerate convergence of PIV image analysis based on confidence statistics

Experiments in Fluids ◽

10.1007/s00348-020-03050-1 ◽

2020 ◽

Vol 61 (10) ◽

Author(s):

M. Edwards ◽

R. Theunissen ◽

C. B. Allen ◽

D. J. Poole

Keyword(s):

Cross Correlation ◽

Particle Image ◽

Field Of View ◽

Steady Flows ◽

Spatial Displacement ◽

Temporal Fluctuations ◽

Correlation Operator ◽

Image Velocimetry ◽

Accelerate Convergence ◽

Image Pairs

Abstract This paper presents a method which allows for a reduced portion of a particle image velocimetry (PIV) image to be analysed, without introducing numerical artefacts near the edges of the reduced region. Based on confidence intervals of statistics of interest, such a region can be determined automatically depending on user-imposed confidence requirements, allowing for already satisfactorily converged regions of the field of view to be neglected in further analysis, offering significant computational benefits. Temporal fluctuations of the flow are unavoidable even for very steady flows, and the magnitude of such fluctuations will naturally vary over the domain. Moreover, the non-linear modulation effects of the cross-correlation operator exacerbate the perceived temporal fluctuations in regions of strong spatial displacement gradients. It follows, therefore, that steady, uniform, flow regions will require fewer contributing images than their less steady, spatially fluctuating, counterparts within the same field of view, and hence the further analysis of image pairs may be solely driven by small, isolated, non-converged regions. In this paper, a methodology is presented which allows these non-converged regions to be identified and subsequently analysed in isolation from the rest of the image, while ensuring that such localised analysis is not adversely affected by the reduced analysis region, i.e. does not introduce boundary effects, thus accelerating the analysis procedure considerably. Via experimental analysis, it is shown that under typical conditions a 44% reduction in the required number of correlations for an ensemble solution is achieved, compared to conventional image processing routines while maintaining a specified level of confidence over the domain. Graphic abstract

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ACCURACY ASSESSMENT OF A UAV-BASED LANDSLIDE MONITORING SYSTEM

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b5-895-2016 ◽

2016 ◽

Vol XLI-B5 ◽

pp. 895-902 ◽

Cited By ~ 4

Author(s):

M. V. Peppa ◽

J. P. Mills ◽

P. Moore ◽

P. E. Miller ◽

J. E. Chambers

Keyword(s):

Image Matching ◽

Accuracy Assessment ◽

Bundle Adjustment ◽

Landslide Monitoring ◽

Control Points ◽

Error Assessment ◽

Ground Sample ◽

Ground Control Points ◽

Pixel Image ◽

Spatio Temporal

Landslides are hazardous events with often disastrous consequences. Monitoring landslides with observations of high spatio-temporal resolution can help mitigate such hazards. Mini unmanned aerial vehicles (UAVs) complemented by structure-from-motion (SfM) photogrammetry and modern per-pixel image matching algorithms can deliver a time-series of landslide elevation models in an automated and inexpensive way. This research investigates the potential of a mini UAV, equipped with a Panasonic Lumix DMC-LX5 compact camera, to provide surface deformations at acceptable levels of accuracy for landslide assessment. The study adopts a self-calibrating bundle adjustment-SfM pipeline using ground control points (GCPs). It evaluates misalignment biases and unresolved systematic errors that are transferred through the SfM process into the derived elevation models. To cross-validate the research outputs, results are compared to benchmark observations obtained by standard surveying techniques. The data is collected with 6 cm ground sample distance (GSD) and is shown to achieve planimetric and vertical accuracy of a few centimetres at independent check points (ICPs). The co-registration error of the generated elevation models is also examined in areas of stable terrain. Through this error assessment, the study estimates that the vertical sensitivity to real terrain change of the tested landslide is equal to 9 cm.

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An Impact Location Algorithm for Spacecraft Stiffened Structure Based on Posterior Possibility Correlation

Sensors ◽

10.3390/s20020368 ◽

2020 ◽

Vol 20 (2) ◽

pp. 368 ◽

Cited By ~ 3

Author(s):

Lei Qi ◽

Zhoumo Zeng ◽

Lichen Sun ◽

Xiaobo Rui ◽

Fan Fan ◽

...

Keyword(s):

Posterior Probability ◽

Cross Correlation ◽

Bayesian Posterior Probability ◽

Probability Method ◽

Stiffened Plate ◽

Plate Structures ◽

Impact Location ◽

Weight Method ◽

Location Algorithm ◽

The Impact

In order to ensure the safety of spacecrafts in orbit, impact location is an important part of structural health monitoring systems. In this paper, an impact location algorithm based on posterior probability correlation is proposed to solve the problem, that is, the impact point in the stiffened structure of a spacecraft is difficult to locate. The algorithm combines the Gaussian cross-correlation possibility weight method and the Bayesian posterior probability method. The cross-correlation possibility weight superposition based on grids was used to reduce the dependence of the accuracy of time difference extraction. Gaussian and normalized fitting were used to compensate the reflection, modal transformation, and amplitude attenuation of a stiffened plate. The location result was further optimized by the posterior probability. The proposed algorithm can be applied to the impact source localization of complex stiffened plate structures. The experiment results showed that the average location error can be 2.57 cm with proper sensor network schemes.

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A 3D Reconstruction Pipeline of Urban Drainage Pipes Based on MultiviewImage Matching Using Low-Cost Panoramic Video Cameras

Water ◽

10.3390/w11102101 ◽

2019 ◽

Vol 11 (10) ◽

pp. 2101 ◽

Cited By ~ 1

Author(s):

Zhang ◽

Zhao ◽

Hu ◽

Wang ◽

Ai ◽

...

Keyword(s):

3D Reconstruction ◽

High Precision ◽

Image Matching ◽

Low Cost ◽

Geometric Distortion ◽

Urban Drainage ◽

Affine Invariant ◽

Pipe Inspection ◽

Video Cameras ◽

Panoramic Video

Urban drainage pipe networks have complex spatial contributions, andthey are now facing problems such as damage, defects, and aging. A rapid and high-precision pipe inspection strategy is thekey to ensuring thesustainable development of urban water supply and drainage system. In this paper, a three-dimensional (3D) reconstruction pipeline of urban drainage pipes based on multiview image matching using low-cost panoramic video cameras is proposed, which provides an innovative technical approach for pipe inspection. Firstly, we extracted frames from the panoramic video of the pipes andcorrected the geometric distortion using a spherical reprojection to obtain multiview pipe images. Second, the robust feature matching method using support lines and affine-invariant ratios isintroduced to conduct pipe image matching. Finally, the photogrammetric processing, using structure from motion (SfM) and dense reconstruction, wasintroduced to achieve the 3D modeling of drainage pipes. Several typical drainage pipes and shafts of the real scenes were taken for the 3D reconstruction experiments. Theresults show that our strategy can realize high-precision 3D reconstruction of different types of pipes, which can provide effective technical support for rapid and efficient inspection of urban pipes with broad application prospects in the daily management of sustainable urban drainage systems (SUDSs).

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