Simulated Synthetic Aperture Research Articles

Modified multi-element synthetic transmit aperture method for ultrasound imaging: A tissue phantom study

The paper presents the modified multi-element synthetic transmit aperture (MSTA) method for ultrasound imaging. It is based on coherent summation of RF echo signals with apodization weights taking into account the finite size of the transmit subaperture and of the receive element. The work presents extension of the previous study where the modified synthetic transmit aperture (STA) method was considered and verified [1]. In the case of MSTA algorithm the apodization weights were calculated for each imaging point and all combinations of the transmit subaperture and receive element using their angular directivity functions (ADFs). The ADFs were obtained from the exact solution of the corresponding mixed boundary-value problem for periodic baffle system modeling the transducer array. Performance of the developed method was tested using Field II simulated synthetic aperture data of point reflectors for 4MHz 128-element transducer array with 0.3mm pitch and 0.02mm kerf to estimate the visualization depth and lateral resolution. Also experimentally determined data of the tissue-mimicking phantom (Dansk Fantom Service, model 571) obtained using 128 elements, 4MHz, linear transducer array (model L14-5/38) and Ultrasonix SonixTOUCH Research platform were used for qualitative assessment of imaging contrast improvement. Comparison of the results obtained by the modified and conventional MSTA algorithms indicated 15dB improvement of the noise reduction in the vicinity of transducer’s surface (1mm depth), and concurrent increase in the visualization depth (86% augment of the scattered amplitude at the depth of 90mm). However, this increase was achieved at the expense of minor degradation of the lateral resolution of approximately 8% at the depth of 50mm and 5% at the depth of 90mm.

Modified synthetic transmit aperture algorithm for ultrasound imaging

The modified synthetic transmit aperture (STA) algorithm is described. The primary goal of this work was to assess the possibility to improve the image quality achievable using synthetic aperture (SA) approach and to evaluate the performance and the clinical applicability of the modified algorithm using phantoms. The modified algorithm is based on the coherent summation of back-scattered RF echo signals with weights calculated for each point in the image and for all possible combinations of the transmit–receive pairs. The weights are calculated using the angular directivity functions of the transmit–receive elements, which are approximated by a far-field radiation pattern of a narrow strip transducer element vibrating with uniform pressure amplitude over its width. In this way, the algorithm takes into account the finite aperture of each individual element in the imaging transducer array. The performance of the approach developed was tested using FIELD II simulated synthetic aperture data of the point reflectors, which allowed the visualization (penetration) depth and lateral resolution to be estimated. Also, both simulated and measured data of cyst phantom were used for qualitative assessment of the imaging contrast improvement. The experimental data were obtained using 128 elements, 4 MHz, linear transducer array of the Ultrasonix research platform. The comparison of the results obtained using the modified and conventional (unweighted) STA algorithms revealed that the modified STA exhibited an increase in the penetration depth accompanied by a minor, yet discernible upon the closer examination, degradation in lateral resolution, mainly in the proximity of the transducer aperture. Overall, however, a considerable (12 dB) improvement in the image quality, particularly in the immediate vicinity of the transducer’s surface was demonstrated. The modified STA method holds promise to be of clinical importance, especially in the applications where the quality of the “near-field” image, that is the image in the immediate vicinity of the scanhead is of critical importance such as for instance in skin- and breast-examinations.

A new signal model for a wideband synthetic aperture imaging sensor

A new signal model was developed to replace the traditional one that is based on the go-stop-go assumptions (the go-stop-go model for short) for a wideband synthetic aperture imaging sensor. Using the new model, we traced the time line of the transmitted signal with a given pulse width, round trip time delay of the signal between the sensor and target, and receiving signal with a fixed pulse duration. The spatial displacement of the senor along the time line was calculated. Then, we obtained the two-dimensional spectrum of an individual target and utilized the two-dimensional joint stationary phase method to solve the spectrum. Incorporating the spectrum with available imaging algorithms, we were able to focus targets in a scene. The performance of the model was investigated by analyzing simulated wideband synthetic aperture radar and synthetic aperture sonar data. In the simulations, the imaging algorithms with the new or go-stop-go model were implemented and outputs compared. Results were very promising.

Exploitation of Ship Scattering in Polarimetric SAR for an Improved Classification Under High Clutter Conditions

This paper evaluates the potentialities of polarimetric ship scattering for basing classification methods that provide reasonable performance within cluttered scenes. Both simulated and airborne polarimetric synthetic aperture radar (SAR) images have been used to validate the conclusions of a previous phenomenological study. Numerical simulations have been carried out with GRECOSAR, a polarimetric interferometric SAR simulation tool that is able to process highly complex targets with a fast and accurate radar-cross-section prediction module. A representative set of scenarios has been defined, which includes various realistic ship models, sea states, and imaging geometries. In all of them, a two-scale sea surface model precisely accounting for sea-ship interaction and sea clutter has been added. The analysis of different images has shown that, with an adequate spatial resolution, ships may be characterized by a particular spatial arrangement and polarization state distribution of dominant scattering centers. This feature has allowed one to propose a new classification algorithm, which shows a promising behavior after various preliminary tests. In this paper, the performance of this technique is further evaluated with realistic clutter. The results show that robust classification is possible even in highly cluttered scenes if quad-pol imagery is available. On the contrary, in low clutter conditions, the usage of less restrictive solutions, like circular dual-pol schemes, is feasible and may still get an acceptable performance.

Least Squares-Based Filter for Remote SensingImage Noise Reduction

The Vondrak filter is a unique technique for smoothing data. The filter aims to achieve a balance between the fidelity and the smoothness of the filtered results. It can therefore preserve the original attributes of the observational data while, at the same time, smooth out the noise. We reformulate the 1-D Vondrak filter that has been widely used in data processing in fields such as astronomy and geophysics and then extend it into two dimensions. The method of conjugate gradients is used to solve the least squares optimization problem. The proposed 2-D filter is a powerful tool for enhancing the quality of various geoscience and remote sensing data such as satellite images. Various tests with simulated and real synthetic aperture radar interferograms show that the new filter is very effective in removing the noise.

Uncertainty analysis of earthquake source parameters determined from InSAR: A simulation study

We assessed the accuracy of earthquake source parameters inverted from simulated Interferometric Synthetic Aperture Radar (InSAR) data. Using focal mechanisms of Australian earthquakes (1959 to the present), we simulated synthetic two‐pass InSAR observations with realistic spatial noise derived from the characteristics of actual ERS‐2 and ENVISAT InSAR data observed over Australia. The precision of two‐pass satellite SAR interferometry with ERS‐2 and ENVISAT SAR data in the Australian region can approach ±2 mm (1σ) and is routinely at the ±4 mm level. The use of spatially correlated observational weights has minimal impact on the accuracy of earthquake source parameters inverted from InSAR data. In most cases single geometry (i.e., ascending or descending) InSAR observations can be used to accurately determine earthquake source parameters, although typically a combined geometry reduces the source parameter uncertainties by a factor of 1.5. In general, earthquakes of magnitude <4.8 are unlikely to be observable by InSAR although very shallow events would be detectable. InSAR is insensitive to magnitude 6.2 earthquakes deeper than 10 km, and magnitude 5.5 deeper than 6 km. For earthquake magnitudes ≥5.8 (average depth 6.5 km) we could estimate the epicenter of the rupture with an average accuracy of 0.25 km, depth to within 0.5 km and the fault orientation to better than 2°. Our findings, based on simulated Australian earthquakes, are representative of typical intraplate earthquakes and would be valid in many other regions. To date no actual earthquakes have been observed by InSAR in Australia.

Automatic Identification of the Number and Values of Decision Thresholds in the Log-Ratio Image for Change Detection in SAR Images

In this letter, we propose an extension of an automatic and unsupervised change-detection method for synthetic aperture radar images we presented earlier. By analyzing a properly defined cost function, the proposed method allows the automatic detection of the number (zero, one, or two) and the values of the decision thresholds associated with changes (if any) in the log-ratio image. This cost function is the minimum value of the criterion function adopted to select the decision threshold in the log-ratio image according to a modified double-thresholding Kittler-Illingworth algorithm (implemented under the generalized Gaussian assumption for changed and unchanged classes). Experimental results carried out both on real and simulated multitemporal synthetic aperture radar images proved the effectiveness of the proposed automatic method in detecting both the number of changes to be identified (the situation of no changes is also explicitly identified) and the related threshold values

Automated CAD model-based geo-referencing for high-resolution SAR data in urban environments

On the basis of street vector data and computer-aided design models of buildings, simulated synthetic aperture radar (SAR) images are created using a SAR simulator. By comparing image chips from a SAR image to simulated street data, correspondences are found, which are used as the first step for the geo-referencing. Afterwards, the geo-referencing can be improved using control point information, which is provided from correspondences between the images of buildings created from a SAR simulator and the respective sections of unreferenced SAR images. The hardware-accelerated real-time SAR simulator SARViz is used for the simulation. On the basis of this approach, the initial geo-referencing of airborne SAR images can be improved, using even the results of simplified and fast SAR simulation methods.

Polynomial distance classifier correlation filter for pattern recognition.

We introduce what is to our knowledge a new nonlinear shift-invariant classifier called the polynomial distance classifier correlation filter (PDCCF). The underlying theory extends the original linear distance classifier correlation filter [Appl. Opt. 35, 3127 (1996)] to include nonlinear functions of the input pattern. This new filter provides a framework (for combining different classification filters) that takes advantage of the individual filter strengths. In this new filter design, all filters are optimized jointly. We demonstrate the advantage of the new PDCCF method using simulated and real multi-class synthetic aperture radar images.

Improving the false alarm capabilities of the maximum average correlation height correlation filter

We show that the maximum average correlation height (MACH) correlation filter overemphasizes the importance of the average training image leading to poor discrimination of the desired class images from clutter images. To overcome this, two new metrics termed the all image correlation height (AICH) and the modified average similarity measure (MASM) are introduced and optimized in a new correlation de- sign. The resulting filter exhibits improved clutter rejection performance while retaining the attractive distortion tolerance feature of the MACH filter. Simulation results based on a simulated synthetic aperture radar (SAR) image database are presented to illustrate the new filter's proper- ties. © 2000 Society of Photo-Optical Instrumentation Engineers. (S0091-3286(00)01805-5)

Simulated annealing, acceleration techniques, and image restoration

Typically, the linear image restoration problem is an ill-conditioned, underdetermined inverse problem. Here, stabilization is achieved via the introduction of a first-order smoothness constraint which allows the preservation of edges and leads to the minimization of a nonconvex functional. In order to carry through this optimization task, we use stochastic relaxation with annealing. We prefer the Metropolis dynamics to the popular, but computationally much more expensive, Gibbs sampler. Still, Metropolis-type annealing algorithms are also widely reported to exhibit a low convergence rate. Their finite-time behavior is outlined and we investigate some inexpensive acceleration techniques that do not alter their theoretical convergence properties; namely, restriction of the state space to a locally bounded image space and increasing concave transform of the cost functional. Successful experiments about space-variant restoration of simulated synthetic aperture imaging data illustrate the performance of the resulting class of algorithms and show significant benefits in terms of convergence speed.

Comparison of actual and simulated synthetic aperture radar image spectra of ocean waves

We have simulated synthetic aperture radar (SAR) image spectra of ocean waves, which were focused for stationary scenes using three popular formulations of SAR ocean imaging theory: the time‐dependent, velocity‐bunching, and quasi‐linear models. All three models require functional forms for surface wave spectra, modulation transfer functions, and correlation times; these were obtained from data taken during the SAR and X Band Ocean Nonlinearities (SAXON)‐Forschungsplatform Nordsee (FPN) experiment of November 1990. These measurements were made on and near the German research platform Nordsee during the same period of time that SAR images of ocean waves at X, C, and L bands were obtained by aircraft near the tower. We compare the results of our simulations to the actual SAR spectra for a variety of integration times, range‐to‐velocity ratios (R/V), and azimuth angles. We find that all three models reproduce the observed image spectra well when integration times are small and R/V ratios are low to moderate. Some adjustments of the parameters measured on the tower are occasionally necessary in order to produce this agreement, but in most cases these adjustments are small and within measurement errors; in all cases the same parameters suffice for all models. However, we reproduce a result previously obtained by Brüning et al. [1994] that measured modulated transfer functions do not properly account for imagery of range‐traveling waves propagating downwind. We also find that our calculated velocity spreads seem to be too large to reproduce the observations when the significant wave height is above about 1.5 m and R/V is appreciable. For long integration times and high R/V ratios, the velocity‐bunching model smears the spectrum more than the time‐dependent model and more than the observations. We find that the velocity‐bunching formulation is viable up to an integration time that is a function of R/V; for lower ratios, velocity bunching is viable up to longer integration times, and we offer an explanation of why this is so. Finally, we find that for large R/V ratios the quasi‐linear model fails to produce the low‐frequency components observed in actual image spectra and produced by velocity‐bunching and time‐dependent models.

GCP acquisition using simulated SAR and evaluation of GCP matching accuracy with texture features

Abstract A method for ground control point (GCP) acquisition using a simulated synthetic aperture radar (SAR) image derived from a digital elevation model (DEM) is proposed. Also proposed is a method for the evaluation of the accuracy of GCP matching with texture features from a reference GCP chip image. Results from experiments with simulated GCP chip images as reference images and geometrically distorted GCP chip images, derived using simulated SAR images as current images, show good coincidence with GCP matching accuracy in terms of pixel distances between matched GCP points in reference and current chip images and texture features. In particular, the correlation coefficient between the angular second moment (ASM) and the matching accuracy is 0.757, followed by Ent (entropy), Horn (homoginiety), Dis (dissimilarity), Con (contrast), Var (variability coefficient) and Chi (Chi-square), for the skewed images while for the rotated images, Dis shows the highest correlation of 0.628, followed by Horn, Asm, Co...

Adaptive speckle filters and scene heterogeneity

The presence of speckle in radar images makes the radiometric and textural aspects less efficient for class discrimination. Many adaptive filters have been developed for speckle reduction, the most well known of which are analyzed. It is shown that they are based on a test related to the local coefficient of variation of the observed image, which describes the scene heterogeneity. Some practical criteria are introduced to modify the filters in order to make them more efficient. The filters are tested on a simulated synthetic aperture radar (SAR) image and an SAR-580 image. As was expected, the new filters perform better, i.e. they average the homogeneous areas better and preserve texture information, edges, linear features, and point target responses better at the same time. Moreover, they can be adapted to features other than the coefficient of variation to reduce the speckle while preserving the corresponding information. >