Cross-correlation Schemes Research Articles

Prediction of atmospheric motion vectors around typhoons using generative adversarial network

In this study, atmospheric motion vectors (AMVs) were derived from the satellite images predicted using a generative adversarial network (GAN) and a deep multi-scale frame prediction algorithm. The GAN was trained and tested with a sequence of the satellite images of a COMS satellite infrared-window channel under the 68 tropical cyclones. The inputs of the consecutive satellite images with 15-min interval were then processed using the trained GAN model to generate satellite images in the next time steps. To further enhance the model’s predictability, particle image velocimetry based on the theory of cross-correlation schemes was employed to the GAN-generated satellite image sequence and AMVs were produced. The GAN-derived AMVs were validated with the wind fields based on the numerical weather prediction (NWP) and radiosonde observations. The comparisons showed that the GAN-derived AMVs depicted the structure of atmospheric circulations with a certain level of accuracy. Through comparison with the radiosonde observations, the root-mean-square error and the wind speed bias of the GAN-derived AMVs were comparable to, and even smaller than those of the NWP-derived wind fields. The current approach may enhance the accuracy in predicting short-term wind velocity fields, which in turn may provide more realistic inputs in storm surge modeling.

AUTOMATIC EVALUATION OF THE INITIAL GEOPOSITIONING ACCURACY FOR LARGE AREA PLANETARY REMOTE SENSING IMAGES

Abstract. The photogrammetric processing of large area planetary remote sensing images is still a very challenging work. In addition to the lack of ground control data and poor tie points extraction, the insufficient knowledge of the initial geopositioning accuracy of the planetary images also increases the difficulty of processing. This paper presents an automatic evaluation method of the initial geopositioning accuracy for large area planetary remote sensing images. The accuracy evaluation method was conducted through image matching on approximate orthophotos derived using coarse resolution digital elevation model (DEM). To improve the orthophotos generation efficiency of linear pushbroom images, a fast ground-to-image transformation algorithm and multi-threaded parallel computing are adopted. The classical normalized cross correlation (NCC) and pyramid matching schemes are used to perform image matching between overlapping orthophotos. Because the conjugate points on orthophotos contain geographic coordinates, we can derive the statistics information (e.g., maximum errors, mean errors and standard deviation) about the geopositioning accuracy of the planetary images. Although it’s actually an evaluation result of relative accuracy, the quantitative geopositioning accuracy information of stereopairs can be used to (1) specify the search window size and the starting position of conjugate points for tie points extraction; (2) set the weight value of bundle adjustment; and (3) identify images with abnormal geopositioning accuracy. Tens of Mars Express (MEX) High Resolution Stereo Camera (HRSC) images were used to conduct the test. The experimental results demonstrate that the proposed method shows high computational efficiency and automation degree. The automatic evaluation of the initial geopositioning accuracy of the planetary images is helpful to produce large area planetary mapping products.

Atmospheric Motion Vectors Derived from an Infrared Window Channel of a Geostationary Satellite Using Particle Image Velocimetry

AbstractAs the new-generation geostationary satellite Himawari-8 provides a greater frequency and more observation channels than its predecessor, the Multifunctional Transport Satellite series (e.g., MTSAT-2), an opportunity arises to generate atmospheric motion vectors (AMVs) with an increased accuracy and extensive distribution over eastern Asia. In this work AMVs were derived from consecutive images of an infrared-window channel (IR1) of the Himawari-8 satellite using particle image velocimetry (PIV) based on the theory of cross-correlation schemes. A multipass scheme and an adaptive interrogation scheme were also employed to increase spatial resolution and accuracy. For height assignment, an infrared-window method was applied for opaque cloud, while an H2O-intercept method was employed for semitransparent cloud. Validation was conducted by comparing the PIV-derived AMVs with wind fields obtained from NWP analysis, radiosonde observations, and the operational system from the Meteorological Satellite Center (MSC) of the Japan Meteorological Agency (JMA) or JMA/MSC. The comparison of wind velocity maps with the NWP data shows that the PIV-derived AMVs are capable of quantitatively depicting full-field wind field maps and strong jets in atmospheric circulation. Through comparisons with radiosonde observations, the root-mean-square error and wind speed bias (4.29 and −1.05 m s−1) of the PIV-derived AMVs are comparable to, although slightly greater than, that of the NWP data (3.88 and −0.26 m s−1). Based on comparison between the PIV-derived AMVs and wind fields obtained from the JMA/MSC operational system, the PIV-derived AMVs are again comparable, producing a slightly lower error but a larger wind speed bias (−1.05 vs 0.20 m s−1). This also implies that a better height assignment algorithm is necessary.

Passive SAR satellite (PASSAT) system: airborne demonstrator and first results

This paper presents the development and execution of an airborne experimental campaign as part of the continuing investigation of a passive Synthetic Aperture Radar using digital television broadcasting stations as illuminators of opportunity, and micro-/nano-satellite receivers in Low Earth Orbit. For the flight experiments, a hardware demonstrator was developed that utilised two receiving antennas, allowing both cross-correlation and auto-correlation range compression schemes, and was mounted to an airborne platform to image stationary rural areas up to 50 km from the transmitter. This paper presents the first image results of these experiments as well as initial analysis of image formation aspects including, range compression scheme and effects on the image quality of the signal to noise on the reference channel.

Transverse single-shot cross-correlation scheme for laser pulse temporal measurement via planar second harmonic generation.

We present a novel single-shot cross-correlation technique based on the analysis of the transversally emitted second harmonic generation in crystals with random distribution and size of anti-parallel nonlinear domains. We implement it to the measurement of ultrashort laser pulses with unknown temporal duration and shape. We optimize the error of the pulse measurement by controlling the incident angle and beam width. As novelty and unlike the other well-known cross correlation schemes, this technique can be implemented for the temporal characterization of pulses over a very wide dynamic range (30 fs-1ps) and wavelengths (800-2200 nm), using the same crystal and without critical angular or temperature alignment.

Fourier interpolation stochastic optical fluctuation imaging

Stochastic Optical Fluctuation Imaging (SOFI) is a super-resolution fluorescence microscopy technique which allows to enhance the spatial resolution of an image by evaluating the temporal fluctuations of blinking fluorescent emitters. SOFI is not based on the identification and localization of single molecules such as in the widely used Photoactivation Localization Microsopy (PALM) or Stochastic Optical Reconstruction Microscopy (STORM), but computes a superresolved image via temporal cumulants from a recorded movie. A technical challenge hereby is that, when directly applying the SOFI algorithm to a movie of raw images, the pixel size of the final SOFI image is the same as that of the original images, which becomes problematic when the final SOFI resolution is much smaller than this value. In the past, sophisticated cross-correlation schemes have been used for tackling this problem. Here, we present an alternative, exact, straightforward, and simple solution using an interpolation scheme based on Fourier transforms. We exemplify the method on simulated and experimental data.

Static and dynamic light scattering in turbid suspensions

The application of static and dynamic light scattering to many colloidal systems of practical interest has often been considered too complicated due to strong multiple scattering. There are two new approaches to overcome this problem. One of them aims at suppressing contributions from multiple scattering using novel cross-correlation schemes. While this relies on the suppression of multiple scattering, the so-called diffusing wave spectroscopy (DWS) works in the limit of very strong multiple scattering. DWS can be used for the characterization of dynamic and static properties of colloidal systems on a large range of time and length scales ranging from a few Ångstroms to hundreds of nanometers. We demonstrate that a wealth of information can be obtained from these methods on the structure, dynamics, interaction effects, stability, aggregation, and sol-gel transition in colloidal dispersions.

Suppression of multiple scattering by photon cross-correlation techniques

The effectiveness of cross-correlation schemes for suppressing multiple scattering in light scattering measurements has been demonstrated convincingly. Thus, measurements on turbid samples can be analysed as though the samples were transparent, i.e. exhibiting only single scattering. The methods are now being used for new research, particularly in the study of concentrated colloidal dispersions. This article reviews the current state of the field with emphasis on the two-colour and three-dimensional dynamic light scattering techniques. Although these methods were originally designed to suppress multiple scattering in dynamic light scattering, it has recently been recognised that they are also effective in static light scattering. The cross-correlation schemes are compared briefly with other light-scattering methods for studying turbid and opaque samples such as fibre-optic probes and diffusing wave spectroscopy.

Characterization of Turbid Colloidal Suspensions Using Light Scattering Techniques Combined with Cross-Correlation Methods

The ability to characterize colloidal suspensions by means of dynamic light scattering is in general limited to systems with negligible contributions from multiple scattering. For larger particle sizes with high scattering contrast this immediately limits the technique to very low concentrations. A promising solution of this problem is to suppress multiple scattering in dynamic light scattering experiments using cross-correlation schemes. Based on these considerations we have constructed a so-called 3D cross-correlation experiment with which we are able to characterize extremely turbid suspensions. We have measured monomodal and bimodal suspensions of latex particles of relatively high volume fraction. The results show clearly that we are able to measure the dynamic structure factor in concentrated polydisperse suspensions with dynamic light scattering. Combining static and dynamic light scattering measurements for characterizing turbid suspensions the single scattering particle form factor and also the static structure factor can be evaluated. We demonstrate that the implementation of a 3D cross-correlation scheme is a powerful method in suppressing multiple scattering contributions in light scattering experiments and opens a wide field of characterization of colloidal dispersions with high turbidity without having to resort to high dilution.

Photorefractive materials and their applications in optical image processing

A brief review of a band transport model for the photorefractive effect is given. Distinction is made between the influence of intrinsic material dependent parameters and externally controlled parameters on the form of the optical nonlinearity. These considerations are made in the context of dynamic holographic optical processing applications. Examples of adaptive optical and Fourier-plane image processing using four-wave mixing in photorefractive bismuth silicon oxide crystals are discussed. Critical assessment is then made of the use of photorefractive materials in image cross-correlation schemes.

Drift correction in periodic crosscorrelation schemes

In the evaluation of a periodic crosscorrelation for a time-invariant system, a simple-to-instrument method is described for eliminating error terms due to polynomial drift disturbances. The method is based on the periodic input perturbation signal being of inverse repeat form, and leads to the result that polynomial drift up to the rth degree may be eliminated by crosscorrelating over r + 2 half periods with appropriate constant weights associated with each half period.