scholarly journals A Novel Stereo Matching Algorithm for Digital Surface Model (DSM) Generation in Water Areas

2020 ◽  
Vol 12 (5) ◽  
pp. 870 ◽  
Author(s):  
Wenhuan Yang ◽  
Xin Li ◽  
Bo Yang ◽  
Yu Fu
Keyword(s):  
Common Ground ◽  
Stereo Matching ◽  
Final Height ◽  
Block Matching ◽  
Disparity Estimation ◽  
Surface Model ◽  
Seed Point ◽  
Practical Applications ◽  
Dense Matching ◽  
Global Matching

Image dense matching has become one of the widely used means for DSM generation due to its good performance in both accuracy and efficiency. However, for water areas, the most common ground object, accurate disparity estimation is always a challenge to excellent image dense matching methods, as represented by semi-global matching (SGM), due to the poor texture. For this reason, a great deal of manual editing is always inevitable before practical applications. The main reason for this is the lack of uniqueness of matching primitives, with fixed size and shape, used by those methods. In this paper, we propose a novel DSM generation method, namely semi-global and block matching (SGBM), to achieve accurate disparity and height estimation in water areas by adaptive block matching instead of pixel matching. First, the water blocks are extracted by seed point growth, and an adaptive block matching strategy considering geometrical deformations, called end-block matching (EBM), is adopted to achieve accurate disparity estimation. Then, the disparity of all other pixels beyond these water blocks is obtained by SGM. Last, the median value of height of all pixels within the same block is selected as the final height for this block after forward intersection. Experiments are conducted on ZiYuan-3 (ZY-3) stereo images, and the results show that DSM generated by our method in water areas has high accuracy and visual quality.

scholarly journals Multi-Label Learning based Semi-Global Matching Forest

2020 ◽  
Vol 12 (7) ◽  
pp. 1069
Author(s):  
Yuanxin Xia ◽  
Pablo d’Angelo ◽  
Jiaojiao Tian ◽  
Friedrich Fraundorfer ◽  
Peter Reinartz
Keyword(s):  
Random Forest ◽  
Stereo Matching ◽  
Training Sample ◽  
Disparity Estimation ◽  
Good Prediction ◽  
Dense Matching ◽  
Learning Procedure ◽  
Global Matching ◽  
Good Trade ◽  
Label Strategy

Semi-Global Matching (SGM) approximates a 2D Markov Random Field (MRF) via multiple 1D scanline optimizations, which serves as a good trade-off between accuracy and efficiency in dense matching. Nevertheless, the performance is limited due to the simple summation of the aggregated costs from all 1D scanline optimizations for the final disparity estimation. SGM-Forest improves the performance of SGM by training a random forest to predict the best scanline according to each scanline’s disparity proposal. The disparity estimated by the best scanline acts as reference to adaptively adopt close proposals for further post-processing. However, in many cases more than one scanline is capable of providing a good prediction. Training the random forest with only one scanline labeled may limit or even confuse the learning procedure when other scanlines can offer similar contributions. In this paper, we propose a multi-label classification strategy to further improve SGM-Forest. Each training sample is allowed to be described by multiple labels (or zero label) if more than one (or none) scanline gives a proper prediction. We test the proposed method on stereo matching datasets, from Middlebury, ETH3D, EuroSDR image matching benchmark, and the 2019 IEEE GRSS data fusion contest. The result indicates that under the framework of SGM-Forest, the multi-label strategy outperforms the single-label scheme consistently.

scholarly journals A comparison of semiglobal and local dense matching algorithms for surface reconstruction

2014 ◽  
Vol XL-5 ◽  
pp. 187-194 ◽  
Author(s):  
E. Dall'Asta ◽  
R. Roncella
Keyword(s):  
Computer Vision ◽  
Stereo Matching ◽  
Least Square ◽  
Stereo Image ◽  
Dense Matching ◽  
Consistency Constraints ◽  
Global Matching ◽  
Matching Cost ◽  
Software Codes ◽  
Matching Techniques

Encouraged by the growing interest in automatic 3D image-based reconstruction, the development and improvement of robust stereo matching techniques is one of the most investigated research topic of the last years in photogrammetry and computer vision.<br><br> The paper is focused on the comparison of some stereo matching algorithms (local and global) which are very popular both in photogrammetry and computer vision. In particular, the Semi-Global Matching (SGM), which realizes a pixel-wise matching and relies on the application of consistency constraints during the matching cost aggregation, will be discussed.<br><br> The results of some tests performed on real and simulated stereo image datasets, evaluating in particular the accuracy of the obtained digital surface models, will be presented. Several algorithms and different implementation are considered in the comparison, using freeware software codes like MICMAC and OpenCV, commercial software (e.g. Agisoft PhotoScan) and proprietary codes implementing Least Square e Semi-Global Matching algorithms. The comparisons will also consider the completeness and the level of detail within fine structures, and the reliability and repeatability of the obtainable data.

scholarly journals SEMI – GLOBAL MERGING OF DIGITAL SURFACE MODELS FROM MULTIPLE STEREOPAIRS

2017 ◽  
Vol IV-2/W4 ◽  
pp. 267-271
Author(s):  
S. Pang ◽  
X. Hu ◽  
M. Zhang ◽  
L. Ye
Keyword(s):  
Global Optimization ◽  
Optimization Algorithm ◽  
Experimental Results ◽  
Surface Model ◽  
Digital Surface Model ◽  
Global Optimization Algorithm ◽  
Smoothness Constraint ◽  
Dense Matching ◽  
Surface Models ◽  
Global Matching

The semi-global optimization algorithm, which approximates a global 2D smoothness constraint by combining several 1D constraints, has been widely used in the field of image dense matching for digital surface model (DSM) generation. However, due to occlusion, shadow and textureless area of the matching images, some inconsistency may exist in the overlapping areas of different DSMs. To address this problem, based on the DSMs generated by semi-global matching from multiple stereopairs, a novel semi-global merging algorithm is proposed to generate a reliable and consistent DSM in this paper. Two datasets, each covering 1&amp;thinsp;km<sup>2</sup>, are used to validate the proposed method. Experimental results show that the optimal DSM after merging can effectively eliminate the inconsistency and reduce redundancy in the overlapping areas.

scholarly journals An Edge-Sense Bidirectional Pyramid Network for Stereo Matching of VHR Remote Sensing Images

2020 ◽  
Vol 12 (24) ◽  
pp. 4025
Author(s):  
Rongshu Tao ◽  
Yuming Xiang ◽  
Hongjian You
Keyword(s):  
Remote Sensing ◽  
Stereo Matching ◽  
Tall Buildings ◽  
Disparity Estimation ◽  
Complex Structures ◽  
Learning Networks ◽  
Remote Sensing Images ◽  
Essential Step ◽  
Disparity Range ◽  
The Cost

As an essential step in 3D reconstruction, stereo matching still faces unignorable problems due to the high resolution and complex structures of remote sensing images. Especially in occluded areas of tall buildings and textureless areas of waters and woods, precise disparity estimation has become a difficult but important task. In this paper, we develop a novel edge-sense bidirectional pyramid stereo matching network to solve the aforementioned problems. The cost volume is constructed from negative to positive disparities since the disparity range in remote sensing images varies greatly and traditional deep learning networks only work well for positive disparities. Then, the occlusion-aware maps based on the forward-backward consistency assumption are applied to reduce the influence of the occluded area. Moreover, we design an edge-sense smoothness loss to improve the performance of textureless areas while maintaining the main structure. The proposed network is compared with two baselines. The experimental results show that our proposed method outperforms two methods, DenseMapNet and PSMNet, in terms of averaged endpoint error (EPE) and the fraction of erroneous pixels (D1), and the improvements in occluded and textureless areas are significant.

scholarly journals Disparity estimation using Graph cuts for road applications

2021 ◽  
Vol 297 ◽  
pp. 01055
Author(s):  
Mohamed El Ansari ◽  
Ilyas El Jaafari ◽  
Lahcen Koutti
Keyword(s):  
Stereo Matching ◽  
Optimal Solution ◽  
Similarity Criterion ◽  
Graph Cuts ◽  
Search Space ◽  
Disparity Estimation ◽  
Stereo Images ◽  
Disparity Map ◽  
Current Frame ◽  
Edge Points

This paper proposes a new edge based stereo matching approach for road applications. The new approach consists in matching the edge points extracted from the input stereo images using temporal constraints. At the current frame, we propose to estimate a disparity range for each image line based on the disparity map of its preceding one. The stereo images are divided into multiple parts according to the estimated disparity ranges. The optimal solution of each part is independently approximated via the state-of-the-art energy minimization approach Graph cuts. The disparity search space at each image part is very small compared to the global one, which improves the results and reduces the execution time. Furthermore, as a similarity criterion between corresponding edge points, we propose a new cost function based on the intensity, the gradient magnitude and gradient orientation. The proposed method has been tested on virtual stereo images, and it has been compared to a recently proposed method and the results are satisfactory.

scholarly journals A new method for estimating of evapotranspiration and surface soil moisture from optical and thermal infrared measurements: the simplified triangle

2020 ◽  
Author(s):  
Toby N. Carlson ◽  
George Petropoulos
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Heat Fluxes ◽  
Surface Model ◽  
Landsat 8 ◽  
Simple Method ◽  
Practical Applications ◽  
Infrared Measurements

Earth Observation (EO) provides a promising approach towards deriving accurate spatiotemporal estimates of key parameters characterizing land surface interactions, such as latent (LE) and sensible (H) heat fluxes as well as soil moisture content. This paper proposes a very simple method to implement, yet reliable to calculate evapotranspiration fraction (EF) and surface moisture availability (Mo) from remotely sensed imagery of Normalized Difference Vegetation Index (NDVI) and surface radiometric temperature (Tir). The method is unique in that it derives all of its information solely from these two images. As such, it does not depend on knowing ancillary surface or atmospheric parameters, nor does it require the use of a land surface model. The procedure for computing spatiotemporal estimates of these important land surface parameters is outlined herein stepwise for practical application by the user. Moreover, as the newly developedscheme is not tied to any particular sensor, it can also beimplemented with technologically advanced EO sensors launched recently or planned to be launched such as Landsat 8 and Sentinel 3. The latter offers a number of key advantages in terms of future implementation of the method and wider use for research and practical applications alike.

Disparity Surface Reconstruction Based on a Stereo Light Microscope and Laser Fringes

2018 ◽  
Vol 24 (5) ◽  
pp. 503-516
Author(s):  
Yuezong Wang
Keyword(s):  
Surface Reconstruction ◽  
Light Microscope ◽  
Stereo Matching ◽  
Block Matching ◽  
Stereo Image ◽  
Reference Plane ◽  
Motion Direction ◽  
Measuring Techniques ◽  
Novel Method ◽  
Disparity Contours

AbstractMicroscopic vision systems based on a stereo light microscope (SLM) are used in microscopic measuring fields. Conventional measuring methods output the disparity surface based on stereo matching methods; however, these methods require that stereo images contain sufficient distinguishing features. Moreover, matching results typically contain many mismatched points. This paper presents a novel method for disparity surface reconstruction by combining an SLM and laser measuring techniques. The surfaces of small objects are scanned by a laser fringe, and a stereo image sequence containing laser stripes is obtained. The central contours of the laser stripes are extracted, and central contours are derived for alignment. A disparity coordinate system is then defined and used to analyze the relationship between the motion direction and reference plane. Next, the method of aligning disparity contours is proposed. The results show that our method can achieve a precision of ±0.5 pixels and that the real and measured shapes described by the disparity surface are consistent based on our method. Our method is confirmed to perform much better than the conventional block-matching method. The disparity surface output obtained by our method can be used to measure the surface profiles of microscopic objects accurately.

Anthropometry-Based Surface Modeling of the Human Torso

1994 ◽  
Author(s):  
Peng Li ◽  
Peter R. M. Jones
Keyword(s):  
Human Body ◽  
Computer Aided Design ◽  
Three Dimensional ◽  
Human Growth ◽  
Surface Model ◽  
Cross Sectional ◽  
Practical Applications ◽  
Garment Design ◽  
Aided Design ◽  
Reference Body

Abstract There is an increasing need for computerized surface model of the human body in human growth, garment design and ergonomics. However, there is a shortage of three-dimensional (3-D) models of the human body in practical applications. This paper presents a new approach for constructing a 3-D surface model of the human torso using anthropometry. The torso is created by from a reference body of average shape which is represented by a family of cross-sectional curves. The shape and size of the reference body can be modified according to anthropometric data. This approach has been implemented on a personal computer. The resulting 3-D model is a parametric surface based on non-uniform B-splines and can easily be exported to other computer aided design applications.

scholarly journals Child Protection With Muslim Communities: Considerations For Non-Muslim-Based Orthodoxies/Paradigms in Child Welfare and Social Work

2019 ◽  
Vol 50 (4) ◽  
pp. 1201-1218
Author(s):  
Patrick O’Leary ◽  
Mohamad Abdalla ◽  
Aisha Hutchinson ◽  
Jason Squire ◽  
Amy Young
Keyword(s):  
Social Work ◽  
Child Protection ◽  
Common Ground ◽  
Work Practice ◽  
Social Work Practice ◽  
Practical Applications ◽  
Social Work Practitioners ◽  
National Boundaries ◽  
Legal Contexts ◽  
Muslim Communities

Abstract The care and protection of children are a concern that crosses ethnic, religious and national boundaries. How communities act on these concerns are informed by cultural and religious understandings of childhood and protection. Islam has specific teachings that relate to the care and guardianship of children and are interpreted in diverse ways across the Muslim world. Islamic teachings on child-care mostly overlap with Western understandings of child protection, but there can be some contested positions. This creates complexities for social workers intervening in Muslim communities where the basis of their intervention is primarily informed by a non-Muslim paradigm or occurs in secular legal contexts. The purpose of this article is to address at a broad level the issue of how overarching concepts of child protection and Islam influence social work practice with Muslim communities. It addresses a gap in practical applications of the synergy of Islamic thinking with core social work practice in the field of child protection. For effective practice, it is argued that social work practitioners need to consider common ground in Islamic thinking on child protection rather than rely on Western frameworks. This requires further research to build evidence-based practice with Muslim families.

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