scholarly journals SAR Images Co-registration Based on Gradient Descent Optimization

2019 ◽  
Vol 9 (2) ◽  
pp. 2361-2367
Keyword(s):  
Gradient Descent ◽  
Cross Correlation ◽  
Dynamic Method ◽  
Signal To Noise Ratio ◽  
Gaussian Kernel ◽  
Sar Images ◽  
Registration Process ◽  
Coarse Registration ◽  
The Common ◽  
Fine Registration

The target of the registration process is to get the disagreement between two captured images for the same area to candidate the transformation matrix that is used to map the points in one image to its congruent in the other image for the same area. A dynamic method is demonstrated in this paper to improve registration process of SAR images. At first, smoothing filtering is used for noise reduction based on gaussian-kernel filter to set aside the pursue-up amplification of noise. Then; area based matching method, cross correlation, is used to perform a coarse registration. The output of the coarse registration is directly applied to the regular step gradient descent (RSGD) optimizer as a fine registration process. The performance of the demonstrated method was evaluated via comparison with the common used corner detectors (Harris, Minimum Eigenvalues, and FAST). Mean square error (MSE) and peak signal-to-noise ratio (PSNR) are the main factors for the comparison. The results show that the demonstrated approach preserves the robustness of the registration process and minimizes the image noise.

scholarly journals A Point Pattern Chamfer Registration of Optical and SAR Images Based on Mesh Grids

2018 ◽  
Vol 10 (11) ◽  
pp. 1837 ◽  
Author(s):  
Chu He ◽  
Peizhang Fang ◽  
Dehui Xiong ◽  
Wenwei Wang ◽  
Mingsheng Liao
Keyword(s):  
Image Registration ◽  
Feature Matching ◽  
Point Pattern ◽  
Sar Image ◽  
Sar Images ◽  
Coarse Registration ◽  
Feature Based ◽  
Mesh Grid ◽  
Coarse To Fine ◽  
Fine Registration

Automatic image registration of optical-to-Synthetic aperture radar (SAR) images is difficult because of the inconsistency of radiometric and geometric properties between the optical image and the SAR image. The intensity-based methods may require many calculations and be ineffective when there are geometric distortions between these two images. The feature-based methods have high requirements on features, and there are certain challenges in feature extraction and matching. A new automatic optical-to-SAR image registration framework is proposed in this paper. First, modified holistically nested edge detection is employed to detect the main contours in both the optical and SAR images. Second, a mesh grid strategy is presented to perform a coarse-to-fine registration. The coarse registration calculates the feature matching and summarizes the preliminary results for the fine registration process. Finally, moving direct linear transformation is introduced to perform a homography warp to alleviate parallax. The experimental results show the effectiveness and accuracy of our proposed method.

scholarly journals An Experimental Study of a New Keypoint Matching Algorithm for Automatic Point Cloud Registration

2021 ◽  
Vol 10 (4) ◽  
pp. 204
Author(s):  
Ramazan Alper Kuçak ◽  
Serdar Erol ◽  
Bihter Erol
Keyword(s):  
Point Cloud ◽  
Point Clouds ◽  
Data Systems ◽  
Icp Algorithm ◽  
Matching Algorithm ◽  
Suggested Algorithm ◽  
Registration Process ◽  
Building Facade ◽  
Coarse Registration ◽  
Fine Registration

Light detection and ranging (LiDAR) data systems mounted on a moving or stationary platform provide 3D point cloud data for various purposes. In applications where the interested area or object needs to be measured twice or more with a shift, precise registration of the obtained point clouds is crucial for generating a healthy model with the combination of the overlapped point clouds. Automatic registration of the point clouds in the common coordinate system using the iterative closest point (ICP) algorithm or its variants is one of the frequently applied methods in the literature, and a number of studies focus on improving the registration process algorithms for achieving better results. This study proposed and tested a different approach for automatic keypoint detecting and matching in coarse registration of the point clouds before fine registration using the ICP algorithm. In the suggested algorithm, the keypoints were matched considering their geometrical relations expressed by means of the angles and distances among them. Hence, contributing the quality improvement of the 3D model obtained through the fine registration process, which is carried out using the ICP method, was our aim. The performance of the new algorithm was assessed using the root mean square error (RMSE) of the 3D transformation in the rough alignment stage as well as a-prior and a-posterior RMSE values of the ICP algorithm. The new algorithm was also compared with the point feature histogram (PFH) descriptor and matching algorithm, accompanying two commonly used detectors. In result of the comparisons, the superiorities and disadvantages of the suggested algorithm were discussed. The measurements for the datasets employed in the experiments were carried out using scanned data of a 6 cm × 6 cm × 10 cm Aristotle sculpture in the laboratory environment, and a building facade in the outdoor as well as using the publically available Stanford bunny sculpture data. In each case study, the proposed algorithm provided satisfying performance with superior accuracy and less iteration number in the ICP process compared to the other coarse registration methods. From the point clouds where coarse registration has been made with the proposed method, the fine registration accuracies in terms of RMSE values with ICP iterations are calculated as ~0.29 cm for Aristotle and Stanford bunny sculptures, ~2.0 cm for the building facade, respectively.

Weak Transient Electromagnetic Radiation Signal Detection Method Considering the New Watershed Image Segmentation Algorithm

2019 ◽  
Vol 34 (03) ◽  
pp. 2054009
Author(s):  
Wenjun Huo ◽  
Peng Chu ◽  
Kai Wang ◽  
Liangting Fu ◽  
Zhigang Niu ◽  
...  
Keyword(s):  
Electromagnetic Radiation ◽  
Cross Correlation ◽  
Detection Efficiency ◽  
Signal To Noise Ratio ◽  
Estimation Method ◽  
Detection Methods ◽  
Signal To Noise ◽  
Long Distance ◽  
Transient Electromagnetic ◽  
Noise Ratio

In order to study the detection methods of weak transient electromagnetic radiation signals, a detection algorithm integrating generalized cross-correlation and chaotic sequence prediction is proposed in this paper. Based on the dual-antenna test and cross-correlation information estimation method, the detection of aperiodic weak discharge signals under low signal-to-noise ratio is transformed into the estimation of periodic delay parameters, and the noise is reduced at the same time. The feasibility of this method is verified by simulation and experimental analysis. The results show that under the condition of low signal-to-noise ratio, the integrated method can effectively suppress the influence of 10 noise disturbances. It has a high detection probability for weak transient electromagnetic radiation signals, and needs fewer pulse accumulation times, which improves the detection efficiency and is more suitable for long-distance detection of weak electromagnetic radiation sources.

scholarly journals Clustering and Halo Occupation Distribution of Active Galactic Nuclei

2013 ◽  
Vol 9 (S304) ◽  
pp. 243-243
Author(s):  
Takamitsu Miyaji ◽  
M. Krumpe ◽  
A. Coil ◽  
H. Aceves ◽  
B. Husemann
Keyword(s):  
Cross Correlation ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Sloan Digital Sky Survey ◽  
Dark Matter Halo ◽  
Bias Parameter ◽  
X Ray ◽  
Sky Survey ◽  
Galaxy Population ◽  
Halo Occupation Distribution

AbstractWe present the results of our series of studies on correlation function and halo occupation distribution of AGNs utilizing data the ROSAT All-Sky Survey (RASS) and the Sloan Digital Sky Survey (SDSS) in the redshift range of 0.07<z<0.36. In order to improve the signal-to-noise ratio, we take cross-correlation approach, where cross-correlation functions (CCF) between AGNs and much more numerous AGNs are analyzed. The calculated CCFs are analyzed using the Halo Occupation Distribution (HOD) model, where the CCFs are divided into the term contributed by the AGN-galaxy pairs that reside in one dark matter halo (DMH), (the 1-halo term) and those from two different DMHs (the 2-halo term). The 2-halo term is the indicator of the bias parameter, which is a function of the typical mass of the DMHs in which AGNs reside. The combination of the 1-halo and 2-halo terms gives, not only the typical DMH mass, but also how the AGNs are distributed among the DMHs as a function of mass separately for those at the center of the DMHs and satellites. The main results are as follows: (1) the range of typical mass of the DMHs in various sub-samples of AGNs log (MDMH/h−1MΘ) ~ 12.4–13.4, (2) we found a dependence of the AGN bias parameter on the X-ray luminosity of AGNs, while the optical luminosity dependence is not significant probably due to smaller dynamic range in luminosity for the optically-selected sample, and (3) the growth of the number of AGNs per DMH (N (MDMH)) with MDMH is shallow, or even may be flat, contrary to that of the galaxy population in general, which grows with MDMH proportionally, suggesting a suppression of AGN triggering in denser environment. In order to investigate the origin of the X-ray luminosity dependence, we are also investigating the dependence of clustering on the black hole mass and the Eddington ratio, we also present the results of this investigation.

QUANTIFYING STOCHASTIC RESONANCE IN A SINGLE THRESHOLD DETECTOR FOR RANDOM APERIODIC SIGNALS

2004 ◽  
Vol 04 (02) ◽  
pp. L247-L265 ◽  
Author(s):  
ARUNEEMA DAS ◽  
N. G. STOCKS ◽  
A. NIKITIN ◽  
E. L. HINES
Keyword(s):  
Stochastic Resonance ◽  
Cross Correlation ◽  
Signal To Noise Ratio ◽  
Probability Distributions ◽  
Probability Density Functions ◽  
Surprising Result ◽  
Threshold Detector ◽  
Gaussian Form ◽  
Aperiodic Signal

We explore stochastic resonance (SR) effects in a single comparator (threshold detector) driven by either a Gaussian or exponentially distributed aperiodic signal. The behaviour of different performance measures, namely the cross-correlation coefficient (CCC), signal-to-noise ratio (SNR) and mutual information, I, has been investigated. The signals were added to Gaussian noise before being passed through the threshold detector. For the two signals tested, we observe the perhaps surprising result that the SNR never displays SR. However, SR is displayed by both the CCC and I for Gaussian signals. For exponential signals SR is not displayed by any of the measures. By generating signals whose probability distributions have the generalized Gaussian form Ae-|βx|n it is possible to demonstrate that SR ceases to occur if n<1.7. We conclude that SR is only observable in threshold based systems for certain types of aperiodic signal. Specifically, SR is not expected to occur for signals whose probability density functions have long, slowly decaying, tails. We discuss the implication of these results for the role of SR in biological sensory systems.

scholarly journals On cross-correlations, averages and noise in electron microscopy

2019 ◽  
Vol 75 (1) ◽  
pp. 12-18 ◽  
Author(s):  
Michael Radermacher ◽  
Teresa Ruiz
Keyword(s):  
High Resolution ◽  
Cross Correlation ◽  
Signal To Noise Ratio ◽  
3D Structure ◽  
Signal To Noise ◽  
High Resolution Structure ◽  
Multiple Copies ◽  
High Level ◽  
2D Images ◽  
Resolution Structure

Biological samples are radiation-sensitive and require imaging under low-dose conditions to minimize damage. As a result, images contain a high level of noise and exhibit signal-to-noise ratios that are typically significantly smaller than 1. Averaging techniques, either implicit or explicit, are used to overcome the limitations imposed by the high level of noise. Averaging of 2D images showing the same molecule in the same orientation results in highly significant projections. A high-resolution structure can be obtained by combining the information from many single-particle images to determine a 3D structure. Similarly, averaging of multiple copies of macromolecular assembly subvolumes extracted from tomographic reconstructions can lead to a virtually noise-free high-resolution structure. Cross-correlation methods are often used in the alignment and classification steps of averaging processes for both 2D images and 3D volumes. However, the high noise level can bias alignment and certain classification results. While other approaches may be implicitly affected, sensitivity to noise is most apparent in multireference alignments, 3D reference-based projection alignments and projection-based volume alignments. Here, the influence of the image signal-to-noise ratio on the value of the cross-correlation coefficient is analyzed and a method for compensating for this effect is provided.

Picking noisy refraction data using semblance supplemented by a Monte Carlo procedure and spectral balancing

1987 ◽  
Vol 77 (3) ◽  
pp. 942-957
Author(s):  
C. A. Zelt ◽  
J. J. Drew ◽  
M. J. Yedlin ◽  
R. M. Ellis
Keyword(s):  
Monte Carlo ◽  
Cross Correlation ◽  
Signal To Noise Ratio ◽  
Time Shift ◽  
Head Wave ◽  
Signal To Noise ◽  
Seismic Section ◽  
Monte Carlo Procedure ◽  
Noise Ratio ◽  
Refraction Data

Abstract In crustal refraction experiments, the crucial deeply refracted and head wave arrivals often have a low signal-to-noise ratio. A method to aid in the picking of noisy refraction data is presented which is applicable to any branch of a seismic section whose waveform is approximately invariant throughout the branch. The technique exploits the spatial correlation of arrivals and is based on the lateral coherency which results if the refracted arrivals are aligned by applying appropriate time shifts to each trace of the branch. The alignment of arrivals occurs iteratively and is accomplished through a cross-correlation of each trace with the stack of the section of the previous iteration. The iteration yielding the section with the highest degree of lateral coherency (semblance) is used to extract the travel-time pick of each trace. The pick, plus a possible d.c. component, is the negative of the time shift required to achieve arrival alignment. Two modifications can improve the performance of the picking routine. To prevent a cycle skipping problem, a Monte Carlo technique is implemented in which the cross-correlation function is transformed into a probability distribution so that the lag corresponding to the maximum cross-correlation is most probably selected. Second, to increase the coherency of the arrivals, a spectral balancing technique is applied in either the time or frequency domain. The picking routine is applied to both a synthetic and real data example, and the results suggest that the routine can be applied successfully to data with a signal-to-noise ratio as low as one. Also, the Monte Carlo procedure together with spectral balancing increases the final semblance over that obtained with the unmodified method.

scholarly journals Testing general relativity with the Doppler magnification effect

2019 ◽  
Vol 488 (3) ◽  
pp. 3759-3771 ◽  
Author(s):  
Sambatra Andrianomena ◽  
Camille Bonvin ◽  
David Bacon ◽  
Philip Bull ◽  
Chris Clarkson ◽  
...  
Keyword(s):  
General Relativity ◽  
Cross Correlation ◽  
Signal To Noise Ratio ◽  
Density Fluctuations ◽  
Signal To Noise ◽  
Tests Of General Relativity ◽  
Velocity Statistics ◽  
The Cross ◽  
Noise Ratio ◽  
Magnification Effect

ABSTRACT The apparent sizes and brightnesses of galaxies are correlated in a dipolar pattern around matter overdensities in redshift space, appearing larger on their near side and smaller on their far side. The opposite effect occurs for galaxies around an underdense region. These patterns of apparent magnification induce dipole and higher multipole terms in the cross-correlation of galaxy number density fluctuations with galaxy size/brightness (which is sensitive to the convergence field). This provides a means of directly measuring peculiar velocity statistics at low and intermediate redshift, with several advantages for performing cosmological tests of general relativity (GR). In particular, it does not depend on empirically calibrated scaling relations like the Tully–Fisher and Fundamental Plane methods. We show that the next generation of spectroscopic galaxy redshift surveys will be able to measure the Doppler magnification effect with sufficient signal-to-noise ratio to test GR on large scales. We illustrate this with forecasts for the constraints that can be achieved on parametrized deviations from GR for forthcoming low-redshift galaxy surveys with DESI and SKA2. Although the cross-correlation statistic considered has a lower signal-to-noise ratio than RSD, it will be a useful probe of GR since it is sensitive to different systematics.

scholarly journals Signal Processing for Parametric Acoustic Sources Applied to Underwater Communication

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5878
Author(s):  
María Campo-Valera ◽  
Ivan Felis-Enguix ◽  
Isidro Villó-Pérez
Keyword(s):  
Cross Correlation ◽  
Sound Propagation ◽  
Signal To Noise Ratio ◽  
Processing Technique ◽  
Underwater Communication ◽  
Carrier Wave ◽  
Acoustic Communications ◽  
Correlation Processing ◽  
Novel Processing ◽  
Special Relevance

For years, in the field of underwater acoustics, a line of research with special relevance for applications of environmental monitoring and maritime security has been developed that explores the possibilities of non-linear phenomena of sound propagation, especially referring to the so-called parametric effect or self-modulation. This article shows the results of using a new modulation technique based on sine-sweep signals, compared to classical modulations (FSK and PSK). For each of these modulations, a series of 16-bit strings of information with different frequencies and durations have been performed, with the same 200 kHz carrier wave. All of them have been tested in the Hydroacoustic Laboratory of the CTN and, through the application of cross-correlation processing, the limitations and improvements of this novel processing technique have been evaluated. This allows reaching better limits in discrimination of bits and signal-to-noise ratio used in underwater parametric acoustic communications.

Simultaneous Multicomponent Quantitative Analysis by Infrared Absorption Spectroscopy

1984 ◽  
Vol 38 (5) ◽  
pp. 663-668 ◽  
Author(s):  
Lesia L. Tyson ◽  
Yong-Chien Ling ◽  
Charles K. Mann
Keyword(s):  
Least Squares ◽  
Infrared Absorption ◽  
Cross Correlation ◽  
Signal To Noise Ratio ◽  
Real Data ◽  
Data Handling ◽  
Peak Overlap ◽  
Lipid Mixtures ◽  
Applicable Range ◽  
Better Than

Two data-handling techniques, least-squares fitting and cross-correlation, have been used for three-component analysis under comparable conditions with the use of both simulated and real data Factors considered are the effect of variation in degree of peak overlap, signal-to-noise ratio, the effect of peak width variations when peak maxima occur at the same position, and the effect of varying peak intensities A series of lipid mixtures was analyzed by each method with the use of infrared absorption This permits comparison of these results with earlier reports Both least-squares and cross-correlation can be used with samples that are outside the applicable range of the earlier work In this comparison, the least-squares results are somewhat better than those from cross-correlation

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