Comparison of four techniques for estimating temporal change of seismic velocity with passive image interferometry

Passive image interferometry （PII） is becoming a powerful tool for detecting the temporal variations in the Earth＇s structure, which applies coda wave interferometry to the waveforrns from the cross-correlation of seismic ambient noise. There are four techniques for estimating temporal change of seismic velocity with PII： moving-window cross-correlation technique （MWCCT）, moving-window cross-spectrum technique （MWCST）, stretching technique （ST） and moving-window stretching technique （MWST）. In this paper, we use the continuous seismic records from a typical station pair near the Wenchuan Ms8.0 earthquake fault zone and generate three sets of waveforms by stacking cross-correlation function of ambient noise with different numbers of days, and then apply four techniques to processing the three sets of waveforms and compare their results. Our results indicate that the techniques based on moving-window （MWCCT, MWCST and MWST） are superior in detecting the change of seismic velocity, and the MWCST can give a better estimate of velocity change than the other moving-window techniques due to measurement error. We also investigate the clock errors and their influences on measuring velocity change. We find that when the clock errors are not very large, they have limited impact on the estimate of the velocity change with the moving-window techniques.

Super-resolution processing of passive millimeter-wave images based on conjugate-gradient algorithm

This paper designs a 3 mm radiometer and validate with experiments based on the principle of passive millimeter wave （PMMW） imaging. The poor spatial resolution, which is limited by antenna size, should be improved by post data processing. A conjugate-gradient （CG） algorithm is adopted to circumvent this drawback. Simulation and real data collected in laboratory environment are given, and the results show that the CG algorithm improves the spatial resolution and convergent rate. Further, it can reduce the ringing effects which are caused by regularizing the image restoration. Thus, the CG algorithm is easily implemented for PMMW imaging.

Super-resolution processing of passive millimeter-wave images based on adaptive projected Landweber algorithm

Passive millimeter wave （PMMW） images inherently have the problem of poor resolution owing to limited aperture dimension. Thus, efficient post-processing is necessary to achieve resolution improvement. An adaptive projected Landweber （APL） super-resolution algorithm using a spectral correction procedure, which attempts to combine the strong points of all of the projected Landweber （PL） iteration and the adaptive relaxation parameter adjustment and the spectral correction method, is proposed. In the algorithm, the PL iterations are implemented as the main image restoration scheme and a spectral correction method is included in which the calculated spectrum within the passband is replaced by the known low frequency component. Then, the algorithm updates the relaxation parameter adaptively at each iteration. A qualitative evaluation of this algorithm is performed with simulated data as well as actual radiometer image captured by 91.5 GHz mechanically scanned radiometer. From experiments, it is found that the super-resolution algorithm obtains better results and enhances the resolution and has lower mean square error （MSE）. These constraints and adaptive character and spectral correction procedures speed up the convergence of the Landweber algorithm and reduce the ringing effects that are caused by regularizing the image restoration problem.

Single exposure passive three-dimensional information reconstruction based on an ordinary imaging system

Existing three-dimensional(3D) imaging technologies have issues such as requiring active illumination, multiple exposures, or coding modulation. We propose a passive single 3D imaging method based on an ordinary imaging system.Using the point spread function of the imaging system to realize the non-coding measurement on the target, the full-focus images and depth information of the 3D target can be extracted from a single two-dimensional(2D) image through the compressed sensing algorithm. Simulation and experiments show that this approach can complete passive 3D imaging based on an ordinary imaging system without any coding operations. This method can achieve millimeter-level vertical resolution under single exposure conditions and has the potential for real-time dynamic 3D imaging. It improves the efficiency of 3D information detection, reduces the complexity of the imaging system, and may be of considerable value to the field of computer vision and other related applications.

Lunar noise correlation,imaging and monitoring

Passive seismic techniques have revolutionarised seismology, leading for example to increased resolution in surface wave tomography, to the possibility to monitor changes in the propagation medium, and to many new processing strategies in seismic exploration. Here we review applications of the new techniques to a very particular dataset, namely data from the Apollo 17 lunar network. The special conditions of the lunar noise environment are investigated, illustrating the interplay between the properties of the noise and the ability to reconstruct Green＇s functions. With a dispersion analysis of reconstructed Rayleigh waves new information about the shallow shear velocity structure of the Moon are obtained. Passive image interferometry is used to study the effect of temperature changes in the subsurface on the seismic velocities providing direct observation of a dynamic process in the lunar environment. These applications highlight the potential of passive techniques for terrestrial and planetary seismology.

Passive Seismic Structure Imaging of a Coal Mine by Ambient Noise Seismic Interferometry on a Dense Array

Active source seismic method is generally used to image subsurface structures for resource exploration,including oil,gas and coal.Although it can provide highresolution subsurface structures,due to some economic and environmental restrictions,it is not suitable in some cases.In recent 20 years,passive seismic survey based on ambient noise seismic interferometry(ANSI)has started to be widely used in imaging subsurface structures.In comparison,ANSI does not need active sources and can image subsurface structures at different depths as a lowcost alternative to active seismic exploration.

Optimal Gridding Process for GMI Brightness Temperature Using the Backus−Gilbert Method

Satellite microwave instruments have different field of views(FOVs)in different channels.A direct average technique(“direct method”)is frequently used to generate gridded datasets in the earth science community.A large FOV will measure radiance from outside the area of a designated grid cell.Thus,the direct method will lead to errors in a measurement over a grid cell because some pixels covering areas outside of the cell are involved in the averaging process.The Backus−Gilbert method(BG method)is proposed and demonstrated to minimize those uncertainties.Three sampling resolutions(6.5 km×6.0 km,11.5 km×6.0 km,13.0 km×6.0 km)are analyzed based on the scanning characteristics of the Global Precipitation Measurement(GPM)Microwave Imager(GMI)18.9-GHz channel.Brightness temperatures(TBs)at 0.5 km×0.5 km resolution over eastern China are used to obtain synthetic 18.9-GHz TBs at the three sampling resolutions.The direct and BG methods are both applied to create a 25 km×25 km gridded dataset and their related uncertainties are analyzed.Results indicate the error variances with the direct method are 3.00,3.68 and 4.99 K2 at the three sampling resolutions,respectively.By contrast,the BG method leads to a much smaller error variance than the direct method,especially over areas with a large TB gradient.Two GMI orbital measurements are applied to verify the BG method for gridding process is reliable.The BG method could be utilized for general purpose of creating a gridded dataset.

Copy-Move Forgery Verification in Images Using Local Feature Extractors and Optimized Classifiers

Passive image forgery detection methods that identify forgeries without prior knowledge have become a key research focus.In copy-move forgery,the assailant intends to hide a portion of an image by pasting other portions of the same image.The detection of such manipulations in images has great demand in legal evidence,forensic investigation,and many other fields.The paper aims to present copy-move forgery detection algorithms with the help of advanced feature descriptors,such as local ternary pattern,local phase quantization,local Gabor binary pattern histogram sequence,Weber local descriptor,and local monotonic pattern,and classifiers such as optimized support vector machine and optimized NBC.The proposed algorithms can classify an image efficiently as either copy-move forged or authenticated,even if the test image is subjected to attacks such as JPEG compression,scaling,rotation,and brightness variation.CoMoFoD,CASIA,and MICC datasets and a combination of CoMoFoD and CASIA datasets images are used to quantify the performance of the proposed algorithms.The proposed algorithms are more efficient than state-of-the-art algorithms even though the suspected image is post-processed.

Image copy-move forgery passive detection based on improved PCNN and self-selected sub-images

Image forgery detection remains a challenging problem.For the most common copy-move forgery detection,the robustness and accuracy of existing methods can still be further improved.To the best of our knowledge,we are the first to propose an image copy-move forgery passive detection method by combining the improved pulse coupled neural network(PCNN)and the self-selected sub-images.Our method has the following steps:First,contour detection is performed on the input color image,and bounding boxes are drawn to frame the contours to form suspected forgery sub-images.Second,by improving PCNN to perform feature extraction of sub-images,the feature invariance of rotation,scaling,noise adding,and so on can be achieved.Finally,the dual feature matching is used to match the features and locate the forgery regions.What’s more,the self-selected sub-images can quickly obtain suspected forgery sub-images and lessen the workload of feature extraction,and the improved PCNN can extract image features with high robustness.Through experiments on the standard image forgery datasets CoMoFoD and CASIA,it is effectively verified that the robustness score and accuracy of proposed method are much higher than the current best method,which is a more efficient image copy-move forgery passive detection method.

一种基于被动图像的陨石坑自主检测方法研究(英文)

Impact craters are commonly found on the surface of planets, satellites, asteroids, and other solar system bodies. The applica- tion field of crater detection algorithm ranges from estimation of planetary surface age to autonomous landing on planets and advanced statistical analyses. this article introduced a method of passive image based crater autonomous detection. Candidate area, is defined as a small rectangular region including craters. The criterion to select a candidate area is there being one or a f...