scholarly journals A Double Epipolar Resampling Approach to Reliable Conjugate Point Extraction for Accurate Kompsat-3/3A Stereo Data Processing

2020 ◽  
Vol 12 (18) ◽  
pp. 2940
Author(s):  
Jaehong Oh ◽  
Youkyung Han
Keyword(s):  
Image Matching ◽  
Traditional Approach ◽  
Conjugate Point ◽  
Conjugate Points ◽  
Stereo Images ◽  
Matching Methods ◽  
Stereo Data ◽  
Extraction Performance ◽  
Along Track ◽  
Bias Compensation

Kompsat-3/3A provides along-track and across-track stereo data for accurate three-dimensional (3D) topographic mapping. Stereo data preprocessing involves conjugate point extraction and acquisition of ground control points (GCPs), rational polynomial coefficient (RPC) bias compensation, and epipolar image resampling. Applications where absolute positional accuracy is not a top priority do not require GCPs, but require precise conjugate points from stereo images for subsequent RPC bias compensation, i.e., relative orientation. Conjugate points are extracted between the original stereo data using image-matching methods by a proper outlier removal process. Inaccurate matching results and potential outliers produce geometric inconsistency in the stereo data. Hence, the reliability of conjugate point extraction must be improved. For this purpose, we proposed to apply the coarse epipolar resampling using raw RPCs before the conjugate point matching. We expect epipolar images with even inaccurate RPCs to show better stereo similarity than the original images, providing better conjugate point extraction. To this end, we carried out the quantitative analysis of the conjugate point extraction performance by comparing the proposed approach using the coarsely epipolar resampled images to the traditional approach using the original stereo images. We tested along-track Kompsat-3 stereo and across-track Kompsat-3A stereo data with four well-known image-matching methods: phase correlation (PC), mutual information (MI), speeded up robust features (SURF), and Harris detector combined with fast retina keypoint (FREAK) descriptor (i.e., Harris). These matching methods were applied to the original stereo images and coarsely resampled epipolar images, and the conjugate point extraction performance was investigated. Experimental results showed that the coarse epipolar image approach was very helpful for accurate conjugate point extraction, realizing highly accurate RPC refinement and sub-pixel y-parallax through fine epipolar image resampling, which was not achievable through the traditional approach. MI and PC provided the most stable results for both along-track and across-track test data with larger patch sizes of more than 400 pixels.

scholarly journals Epipolar Rectification for CARTOSAT-1 Stereo Images Using SIFT and RANSAC

2014 ◽  
Vol XL-8 ◽  
pp. 1095-1098
Author(s):  
A. Akilan ◽  
D. Sudheer Reddy ◽  
V. Nagasubramanian ◽  
P. V. Radhadevi ◽  
G. Varadan
Keyword(s):  
Image Matching ◽  
Computational Effort ◽  
3D Modelling ◽  
High Fidelity ◽  
Stereo Images ◽  
Generation Algorithm ◽  
One Dimensional ◽  
Processing Step ◽  
Along Track ◽  
Modelling Application

Cartosat-1 provides stereo images of spatial resolution 2.5 m with high fidelity of geometry. Stereo camera on the spacecraft has look angles of +26 degree and -5 degree respectively that yields effective along track stereo. Any DSM generation algorithm can use the stereo images for accurate 3D reconstruction and measurement of ground. Dense match points and pixel-wise matching are prerequisite in DSM generation to capture discontinuities and occlusions for accurate 3D modelling application. Epipolar image matching reduces the computational effort from two dimensional area searches to one dimensional. Thus, epipolar rectification is preferred as a pre-processing step for accurate DSM generation. In this paper we explore a method based on SIFT and RANSAC for epipolar rectification of cartosat-1 stereo images.

scholarly journals AN INTEGRATED PHOTOGRAMMETRIC AND PHOTOCLINOMETRIC APPROACH FOR PIXEL-RESOLUTION 3D MODELLING OF LUNAR SURFACE

2018 ◽  
Vol XLII-3 ◽  
pp. 1117-1122
Author(s):  
W. C. Liu ◽  
B. Wu
Keyword(s):  
High Resolution ◽  
Lunar Surface ◽  
Image Matching ◽  
Point Cloud ◽  
3D Modelling ◽  
Conjugate Points ◽  
Stereo Pair ◽  
Pixel Resolution ◽  
Dense Image ◽  
Lunar Reconnaissance Orbiter

High-resolution 3D modelling of lunar surface is important for lunar scientific research and exploration missions. Photogrammetry is known for 3D mapping and modelling from a pair of stereo images based on dense image matching. However dense matching may fail in poorly textured areas and in situations when the image pair has large illumination differences. As a result, the actual achievable spatial resolution of the 3D model from photogrammetry is limited by the performance of dense image matching. On the other hand, photoclinometry (i.e., shape from shading) is characterised by its ability to recover pixel-wise surface shapes based on image intensity and imaging conditions such as illumination and viewing directions. More robust shape reconstruction through photoclinometry can be achieved by incorporating images acquired under different illumination conditions (i.e., photometric stereo). Introducing photoclinometry into photogrammetric processing can therefore effectively increase the achievable resolution of the mapping result while maintaining its overall accuracy. This research presents an integrated photogrammetric and photoclinometric approach for pixel-resolution 3D modelling of the lunar surface. First, photoclinometry is interacted with stereo image matching to create robust and spatially well distributed dense conjugate points. Then, based on the 3D point cloud derived from photogrammetric processing of the dense conjugate points, photoclinometry is further introduced to derive the 3D positions of the unmatched points and to refine the final point cloud. The approach is able to produce one 3D point for each image pixel within the overlapping area of the stereo pair so that to obtain pixel-resolution 3D models. Experiments using the Lunar Reconnaissance Orbiter Camera - Narrow Angle Camera (LROC NAC) images show the superior performances of the approach compared with traditional photogrammetric technique. The results and findings from this research contribute to optimal exploitation of image information for high-resolution 3D modelling of the lunar surface, which is of significance for the advancement of lunar and planetary mapping.

scholarly journals III. On certain ternary alloys. Part V. Determination of various critical curves, and their tie-lines and limiting points

1892 ◽  
Vol 50 (302-307) ◽  
pp. 372-395 ◽  
Keyword(s):  
Graphical Representation ◽  
Conjugate Point ◽  
Critical Curve ◽  
Ternary Mixtures ◽  
Ternary Alloys ◽  
Conjugate Points ◽  
Critical Curves ◽  
Tie Lines ◽  
Tie Line

The triangular method of graphical representation suggested by Sir G. G. Stokes, and described in Part IV (‘Roy. Soc. Proc.,’ vol. 49, p. 174), substantially amounts to the tracing out of a curve (“ critical curve”) which shall express the saturation of the solvent C with a mixture in given variable proportions of the other two constituents, A, B ; the variation being such that any given point on the curve is related to some other point (“ conjugate point ”) in a way given by the consideration that all mixtures of the three constituents, A, B, C, represented by points lying on the line (“ tie-line ”) joining these two conjugate points (“ ideal ” alloys, or mixtures), will separate into two different ternary mixtures corresponding with the two points respectively ; whereas any mixture of the same constituents, repre­sented by a point lying outside the critical curve, will form a “ real ” alloy, or mixture, not separating spontaneously into two different fluids but existing as a stable homogeneous whole.

Conjugate points for fractional differential equations

2014 ◽  
Vol 17 (3) ◽  
Author(s):  
Paul Eloe ◽  
Jeffrey Neugebauer
Keyword(s):  
Differential Equations ◽  
Boundary Value Problem ◽  
Boundary Value ◽  
Conjugate Point ◽  
Sufficient Conditions ◽  
Conjugate Points ◽  
Existence Of A Solution ◽  
Nonlinear Fractional Differential Equation ◽  
Fractional Differential ◽  
Linear Differential

AbstractLet b > 0. Let 1 < α ≤ 2. The theory of u 0-positive operators with respect to a cone in a Banach space is applied to study the conjugate boundary value problem for Riemann-Liouville fractional linear differential equations D 0+α u + λp(t)u = 0, 0 < t < b, satisfying the conjugate boundary conditions u(0) = u(b) = 0. The first extremal point, or conjugate point, of the conjugate boundary value problem is defined and criteria are established to characterize the conjugate point. As an application, a fixed point theorem is applied to give sufficient conditions for existence of a solution of a related boundary value problem for a nonlinear fractional differential equation.

scholarly journals Global Distribution Adjustment and Nonlinear Feature Transformation for Automatic Colorization

2018 ◽  
Vol 2018 ◽  
pp. 1-15
Author(s):  
Terumasa Aoki ◽  
Van Nguyen
Keyword(s):  
Image Matching ◽  
Feature Vector ◽  
Color Image ◽  
Computational Cost ◽  
Texture Feature ◽  
Feature Descriptor ◽  
Matching Methods ◽  
Nonlinear Feature ◽  
Efficient Matching ◽  
Descriptive Feature

Automatic colorization is generally classified into two groups: propagation-based methods and reference-based methods. In reference-based automatic colorization methods, color image(s) are used as reference(s) to reconstruct original color of a gray target image. The most important task here is to find the best matching pairs for all pixels between reference and target images in order to transfer color information from reference to target pixels. A lot of attractive local feature-based image matching methods have already been developed for the last two decades. Unfortunately, as far as we know, there are no optimal matching methods for automatic colorization because the requirements for pixel matching in automatic colorization are wholly different from those for traditional image matching. To design an efficient matching algorithm for automatic colorization, clustering pixel with low computational cost and generating descriptive feature vector are the most important challenges to be solved. In this paper, we present a novel method to address these two problems. In particular, our work concentrates on solving the second problem (designing a descriptive feature vector); namely, we will discuss how to learn a descriptive texture feature using scaled sparse texture feature combining with a nonlinear transformation to construct an optimal feature descriptor. Our experimental results show our proposed method outperforms the state-of-the-art methods in terms of robustness for color reconstruction for automatic colorization applications.

scholarly journals Impact of the Acquisition Geometry of Very High-Resolution Pléiades Imagery on the Accuracy of Canopy Height Models over Forested Alpine Regions

2018 ◽  
Vol 10 (10) ◽  
pp. 1542 ◽  
Author(s):  
Livia Piermattei ◽  
Mauro Marty ◽  
Wilfried Karel ◽  
Camillo Ressl ◽  
Markus Hollaus ◽  
...  
Keyword(s):  
High Resolution ◽  
Image Matching ◽  
Canopy Height ◽  
Forest Monitoring ◽  
Aerial Image ◽  
Stereo Pair ◽  
Stereo Images ◽  
Mountain Areas ◽  
Surface Models ◽  
The Impact

This work focuses on the accuracy estimation of canopy height models (CHMs) derived from image matching of Pléiades stereo imagery over forested mountain areas. To determine the height above ground and hence canopy height in forest areas, we use normalised digital surface models (nDSMs), computed as the differences between external high-resolution digital terrain models (DTMs) and digital surface models (DSMs) from Pléiades image matching. With the overall goal of testing the operational feasibility of Pléiades images for forest monitoring over mountain areas, two questions guide this work whose answers can help in identifying the optimal acquisition planning to derive CHMs. Specifically, we want to assess (1) the benefit of using tri-stereo images instead of stereo pairs, and (2) the impact of different viewing angles and topography. To answer the first question, we acquired new Pléiades data over a study site in Canton Ticino (Switzerland), and we compare the accuracies of CHMs from Pléiades tri-stereo and from each stereo pair combination. We perform the investigation on different viewing angles over a study area near Ljubljana (Slovenia), where three stereo pairs were acquired at one-day offsets. We focus the analyses on open stable and on tree covered areas. To evaluate the accuracy of Pléiades CHMs, we use CHMs from aerial image matching and airborne laser scanning as reference for the Ticino and Ljubljana study areas, respectively. For the two study areas, the statistics of the nDSMs in stable areas show median values close to the expected value of zero. The smallest standard deviation based on the median of absolute differences (σMAD) was 0.80 m for the forward-backward image pair in Ticino and 0.29 m in Ljubljana for the stereo images with the smallest absolute across-track angle (−5.3°). The differences between the highest accuracy Pléiades CHMs and their reference CHMs show a median of 0.02 m in Ticino with a σMAD of 1.90 m and in Ljubljana a median of 0.32 m with a σMAD of 3.79 m. The discrepancies between these results are most likely attributed to differences in forest structure, particularly tree height, density, and forest gaps. Furthermore, it should be taken into account that temporal vegetational changes between the Pléiades and reference data acquisitions introduce additional, spurious CHM differences. Overall, for narrow forward–backward angle of convergence (12°) and based on the used software and workflow to generate the nDSMs from Pléiades images, the results show that the differences between tri-stereo and stereo matching are rather small in terms of accuracy and completeness of the CHM/nDSMs. Therefore, a small angle of convergence does not constitute a major limiting factor. More relevant is the impact of a large across-track angle (19°), which considerably reduces the quality of Pléiades CHMs/nDSMs.

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