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.

35 GHz Vivaldi Fed Antenna Design for Passive Millimeter Wave Imaging System in Ka Band

This antenna will be used for PMWIS （passive millimeter wave imaging system） which has 35 GHz operating frequency described as Ka Band. The antenna should work in that specific frequency because of having low attenuation in that region according to frequency behavior in misty conditions. Antenna also should have approximately 50 ohm input impedance value so that perfect matching to the active circuits will occur. The input reflection coefficient, S11, has to be under -20 dB and the gain of the antenna, has to be over 10 dB value for better efficiency. Microstrip Vivaldi Fed Antenna provides all of the conditions for imaging system, was designed by using Antenna Magus Computer Program and later it was designed in detail with Computer Simulation Technology Studio Suite Computer Program. The last format of the VFA has -23.1 dB input reflection coefficient, 48.55 ohm input impedance and 12.3 dB gain for 35 GHz OF. It is ready to connect to the LNA and detector, which are active circuits of the PMWIS. At the end, the detector will be connected to the VA and computer. The receiver of PMWIS is composed to the VFA connected to the other equipment that is defined above will scan elevation and azimuth angles, as a result; the VA will transfer the signals to the computer. Computer will show the user the scanning area image. In this system, antenna is the most important section and particular attention was given to the antenna in this study.

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.

Long wavelength infrared metalens fabricated by photolithography

Metasurfaces in the long wave infrared(LWIR)spectrum hold great potential for applications in ther-mal imaging,atmospheric remote sensing,and target identification,among others.In this study,we designed and experimentally demonstrated a 4 mm size,all-silicon metasurface metalens with large depth of focus opera-tional across a broadband range from 9µm to 11.5µm.The experimental results confirm effective focusing and imaging capabilities of the metalens in LWIR region,thus paving the way for practical LWIR applications of met-alens technology.

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.

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.

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.

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.

Method of Passive Image Based Crater Autonomous Detection

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...

Study of SAR imaging with COMPASS signal

A concept of space-surface bistatic synthetic aperture radar (SS-BSAR) passive imaging system is proposed,which is parasitic on the signal of COMPASS Navigation Satellite System (CNSS).The feasibility is demonstrated by analyzing the signal ambiguity function and the range resolution as well as the system topology.Due to the multiple peaks of signal in the auto-correlation function,a new correlation is used to remove the side-peaks.A double-channel receiver is employed to receive the direct satellite signal and the ground reflected signal.The direct signal is a reference signal in range compression,and may also be used for transmitter-receiver signal synchronization.The reflected signal is raw data collected for imaging.Then,a modified range-Doppler imaging algorithm is derived based on the system geometric models and BSAR imaging principle.The proposed algorithm is verified via signal simulation.The work in this paper is of great value to the further use of COMPASS signal,as well as other global navigation satellite signals in passive imaging.

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.

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.

Detecting Shifted Double JPEG Compression Tampering Utilizing Both Intra-Block and Inter-Block Correlations

Copy-paste forgery is a very common type of forgery in JPEG images.The tampered patch has always suffered from JPEG compression twice with inconsistent block segmentation.This phenomenon in JPEG image forgeries is called the shifted double JPEG(SDJPEG) compression.Detection of SDJPEG compressed image patches can make crucial contribution to detect and locate the tampered region.However,the existing SDJPEG compression tampering detection methods cannot achieve satisfactory results especially when the tampered region is small.In this paper,an effective SDJPEG compression tampering detection method utilizing both intra-block and inter-block correlations is proposed.Statistical artifacts are left by the SDJPEG compression among the magnitudes of JPEG quantized discrete cosine transform(DCT) coefficients.Firstly,difference 2D arrays,which describe the differences between the magnitudes of neighboring JPEG quantized DCT coefficients on the intrablock and inter-block,are used to enhance the SDJPEG compression artifacts.Then,the thresholding technique is used to deal with these difference 2D arrays for reducing computational cost.After that,co-occurrence matrix is used to model these difference 2D arrays so as to take advantage of second-order statistics.All elements of these co-occurrence matrices are served as features for SDJPEG compression tampering detection.Finally,support vector machine(SVM) classifier is employed to distinguish the SDJPEG compressed image patches from the single JPEG compressed image patches using the developed feature set.Experimental results demonstrate the efficiency of the proposed method.

Asynchronous rotation scan for synthetic aperture interferometric radiometer

Synthetic aperture interferometric technique has wide applications in optics,radio astronomy and mi-crowave remote sensing areas.With the increasing demands of high resolution imaging observation,a new time-sharing sampling scheme of asynchronous rotation scan is proposed to meet the technical challenge of achieving a large equivalent aperture and overcome the operating barriers of space borne application.This configuration is basically composed by two asynchronously and concentrically ro-tating antenna groups,whose revolving radii and speeds are different.The synthetic aperture system with asynchronous rotation scanning scheme can effectively solve the trade-off problem of system complexity,and greatly simplify the system hardware at the cost of sacrificing a certain time resolution.The basic rules and design methods of asynchronous rotation scan are investigated The Gridding method is introduced to inverse the spiral sampling data for image reconstruction.The potential ap-plications of geostationary orbit(GEO)earth observation and solar polar orbit(SPO)plasma cloud observation are explored with numerical simulations to validate the significance and feasibility of this new imaging configuration.