A real-time back projection imaging algorithm for impulse surface penetrating radar

In order to solve the problems that the existing high squint missile-borne synthetic aperture radar( SAR) algorithm can not deal with too high squint angle,and that the calculated amount of traditional back-projection( BP) imaging algorithm is too large,as well as that the current fast BP algorithm can not process the echo data in parallel,an improved approximate forward looking missile-borne SAR back-projection imaging algorithm which can process echo data in parallel was proposed. According to geometrical relationship of approximate forward looking missile-borne SAR,an echo signal model was established. And the imaging area was divided to equidistance strip in range along the distance direction. The image was split when merging sub aperture,and the splitting and merging did not stop until the accuracy of image met the requirements.Next the raw echo data was back projected to each strip for coherent integration,and then the missile-borne SAR image was obtained. If these strips were processed for imaging in parallel,the imaging speed would be further improved. Finally,results of simulation echo data and real echo data validate that the improved algorithm can deal with approximate forward looking scene with 86° squint angle,and it can greatly improve the computation speed compared with that of traditional BP algorithm. Moreover,the computation speed is faster than that of other improved BP algorithms by processing those strips in parallel.

Three-dimensional BP Imaging Algorithm using MIMO System

In this paper, a filtered adjoint inversion scheme for turntable inverse synthetic aperture radar (ISAR) data is derived for three spatial dimensions from a scalar wave equation model. The proposed data inversion scheme motivates the use of filtered back projection (FBP) and convolution back projection (CBP) imaging algorithms. This paper also provides a derivation of a general imaging filter needed for accurate near-field FBP and CBP imaging algorithms, which will be shown to reduce to familiar results found in SWISAR (Spherical-Wave ISAR) imaging.

Stepped frequency continuous wave ground penetrating radar (SFCW-GPR) systems are becoming increasingly popular in the GPR community due to the wider dynamic range and higher immunity to radio interference. The traditional back-projection (BP) algorithm is preferable for SFCW-GPR imaging in layered mediums scenarios for its convenience and robustness. However, the existing BP imaging algorithms are usually very computationally intensive, which limits their practical applications to SFCW-GPR imaging. To solve the above problem, a fast SFCW-GPR BP imaging algorithm based on nonuniform fast Fourier transform (NUFFT) technique is proposed in this paper. By reformulating the traditional BP imaging algorithm into the evaluations of NUFFT, the computational efficiency of NUFFT is exploited to reduce the computational complexity of the imaging reconstruction. Both simulation and experimental results have verified the effectiveness and improvement of computational efficiency of the proposed imaging method.

In this research, we propose a real-time spatiotemporal free-fps algorithm based on the multidimensional vector matrix Walsh transform with an adjustable ghost imaging video quality and a frame rate to address the issues of uneven imaging speed, fixed imaging frame rate, and uncomfortable appearance in real-time ghost imaging videos of moving objects. This algorithm utilizes the temporal and spatial correlation of ghost imaging videos to achieve free and adjustable video frame rates in time without being limited by DMD refresh rates. Improving the spatial information of a single frame in space enhances the smoothness of ghost imaging videos, making the appearance of ghost imaging videos more comfortable. To achieve this, a four-dimensional vector Walsh transform kernel matrix is used to transform and reconstruct the high-quality images of the target object. Then the reconstructed high-quality image is spatially interpolated to enhance spatial information. Reasonable frame rate parameters are set based on the corresponding relationship between the detection values of the adjacent frames and speckle, improving the ghost imaging video in both time and space and achieving a smooth real-time ghost imaging video with an adjustable quality and frame rate. The simulation and experimental results of moving objects show that our algorithm solves the limitation of a DMD refresh rate compared with the existing ghost imaging video methods and makes the ghost imaging video more comfortable and smoother in real time. The PSNR of the objective evaluation index is increased by 12%. Regarding a subjective evaluation, this paper proposes an adaptive parameterless evaluation algorithm (APEA) for images with different resolutions based on the NRSS, which improved the structure retention degree by 13% and the Brisque parameter evaluation by 70%. We propose an adaptive parameterless video comfort evaluation algorithm (APVCEA) to evaluate the subjective comfort of ghost imaging videos by 14% compared with traditional methods.

The first quarter of 2007 started as an active season for the real-time image processing community. The annual SPIE Conference on Real-Time Image Processing, which was held in San Jose, CA, highlighted recent developments in this growing branch of image processing. As one of the few regular events with its focus matching that of JRTIP, one witnessed the growth in applications of real-time image and video processing. The conference served as an effective instrument to foster the dissemination of recent results and to leverage the cohesion of the real time image processing community. The preparations for the next SPIE Conference on Real-Time Image Processing in 2008 are already progressing and its call-for-papers is included at the end of this issue. In 2007, JRTIP is going to seek involvement of more scientists in the field of real-time image and video processing. After 1 year of operation, the editors-in-chief have started to recruit additional associate editors to enlarge the expertise base of the editorial board, to solicit manuscript submissions from potential authors, and to make the reviewing process more efficient. Interested colleagues should contact the editors-in-chief expressing their Associate Editor candidature in support of one or more fields within the focus of JRTIP. In addition, they wish to encourage researchers to act as guest editors for special issues on any real-time image or video processing related topics of interest to them. It is possible to schedule two special issues in 2007, provided that a draft call-for-papers is sent to the editors-in-chief as soon as possible. The third issue of JRTIP presents four articles, two are survey papers and two are original research papers. These articles address different real-time image processing perspectives ranging from algorithmic to hardware issues. The first survey paper deals with the real-time filtering in 2D and 3D using ordered statistics that are supported by a rich set of experimental results derived from several algorithmic variations. Performance measurements are used to demonstrate the effect of noise suppression and preservation of fine image structures and to show the DSP implementation of denoising filters. The second survey paper introduces a non-invasive analysis of dynamic processes in living cells using microscopic computer vision techniques for understanding the interactions between cellular and molecular functional units and for providing novel insights into the cell biology. The third article is an original research paper covering a machine vision application involving vision-based position sensing for aerial refueling of unmanned aerial vehicles in real-time. A full image processing chain is investigated and tested in a MATLAB/Simulink soft real-time environment as well as in a Linux/RTAI hard real-time environment. The feasibility of the real-time implementation is shown using off-the-shelf commercial hardware. The fourth article is another original research paper describing a hardware architecture for real-time fractal coding for image compression. The introduced parallel hardware architecture contains units for domain M. F. Carlsohn (&) Ingenieurberatung fur Computer Vision und Bildkommunikation, Am Heiddamm 36g, 28355 Bremen, Germany e-mail: matthias.carlsohn@t-online.de

Ultrasound image fusion for external beam radiotherapy for prostate cancer

Chaos through-wall imaging radar has attracted wide attention due to its inherent low probability of detection/interception, strong anti-jamming, and high resolution. However, the target response is usually overwhelmed by strong clutter. This paper proposes an imaging-then-decomposition method based on two-stage robust principal component analysis (RPCA) to remove the clutter and recover the target image. The proposed method firstly focuses the energy of the preprocessing data by the back-projection imaging algorithm; then, it performs matrix decomposition on the full and the sparse component of the focused data, in succession, by the RPCA algorithm. Simulation and experimental results show that the proposed method can suppress the clutter dramatically and indicate human targets distinctly. Compared with the traditional methods, it has effectiveness and superiority in improving the signal-to-clutter ratio.

In this paper, we propose the two-dimensional imaging response of three-dimensional moving target via synthetic aperture radar (SAR) with back-projection imaging algorithm. Firstly, we analyzed the imaging response for each single echo, which is the intersection of Doppler isodop and iso-range contour. Then, we come up with a focus condition for moving target SAR imaging. Besides, we find that the Doppler frequency will cause a shift and the motion trail of moving target will draw a curve in the imaging result over synthetic aperture time. Meanwhile, we provide the numerical simulation experiments of moving point targets via linear SAR and circular SAR with X-band and THz-band, respectively, to verify the conclusion of moving target imaging response.

Video Synthetic Aperture Radar (SAR) has shown great potential in moving target detection and tracking. At present, most of the existing detection methods focus on the intensity information of the moving target shadow. According to the mechanism of shadow formation, some shadows of moving targets present low contrast, and their boundaries are blurred. Additionally, some objects with low reflectivity show similar features with them. These cause the performance of these methods to degrade. To solve this problem, this paper proposes a new moving target shadow detection method, which consists of background modeling and shadow detection based on intensity information and neighborhood similarity (BIIANS). Firstly, in order to improve the efficiency of image sequence generation, a fast method based on the Back-projection imaging algorithm (f-BP) is proposed. Secondly, due to the low-rank characteristics of stationary objects and the sparsity characteristics of moving target shadows presented in the image sequence, this paper introduces the low-rank sparse decomposition (LRSD) method to perform background modeling for obtaining better background (static objects) and foreground (moving targets) images. Because the shadows of moving targets appear in the same position in the original and the corresponding foreground images, the similarity between them is high and independent of their intensity. Therefore, using the BIIANS method can obtain better shadow detection results. Real W-band data are used to verify the proposed method. The experimental results reveal that the proposed method performs better than the classical methods in suppressing false alarms, missing alarms, and improving integrity.

Ultrawideband pulse radars have a great potential for high-range resolution in near field imaging and can be used for noncontact measuring in precision or specular products such as reflector antennas and aircraft fuselages. We have already proposed a high-speed 3-D imaging algorithm, SEABED, which is based on a reversible transform, which is the boundary scattering transform, between the received signals and the target shape. However, the estimated image with SEABED is unstable with random noise because it utilizes a derivative of the received data. In this paper, we propose a robust 3-D imaging algorithm with an envelope of spheres that completely resolves the instability due to derivative operations. Moreover, to enhance the resolution of estimated images, this method is combined with a direct waveform compensation method that does not sacrifice high-speed calculation. Numerical simulations and an experiment confirm that the proposed method can realize fast, robust, and high-resolution 3-D imaging for arbitrary targets.

Aimed at improving the imaging efficiency of frequency-modulation continuous-wave (FMCW) ground-based synthetic aperture radar (SAR) characterized with lots of data, high resolution and burden processing of imaging algorithm, a real-time imaging processing software architecture based on TMS320C6678 signal processor is proposed in this paper. The multicore parallel processing technology is adopted to resolve the problem of real time imaging and the polar coordinates back-projection algorithm is realized efficiently. Experimental results demonstrate that the real-time processing software can reduce the time consumption significantly and keep the correctness of the imaging results of ground-based SAR.

During monitoring the building fire explosion site, the combustible object may easily collapse, thus changing the distance between the combustible object and radar system. For this reason, the combustible object position in a series of 2-D images obtained by Back Projection (BP) imaging technique is displaced. Based on the fact that the echo intensity of specular reflection is stronger than the echo intensity of diffuse reflection, in this paper, a collapse detection method based on the amplitude variations between two frames is proposed to determine whether the combustible object collapses. Besides, a position compensation method which uses the focusing delay skew to reconstruct the 2-D image is proposed to obtain the real position. The simulation results validate the correctness and feasibility of the algorithm.

该文基于探地雷达(Ground Penetrating Radar, GPR)回波数据之间的互相关性，提出了一种用于抑制GPR成像中杂波干扰的反向投影(Back Projection, BP)成像算法。与标准BP算法相比，该文的互相关反向投影(Cross-correlated Back Projection, CBP)算法增加了数据间互相关运算的步骤，而且无需引入额外的参考信号通道。理论分析和实验结果均表明，CBP算法不仅抑制了标准BP算法成像结果中的杂波干扰，而且在一定程度上提高了成像分辨率。

Interest in 3D medical imaging continues to increase. However, in ultrasound, real-time imaging is an indispensable strength; and real-time 3D ultrasonic imaging is not practical when conventional steered, focused beam techniques are used. This is because the speed of sound severely limits the size of the volume that can be imaged in real time. For real-time 3D imaging, approaches like simultaneous multiple beams or holography have been considered but never commercially implemented for, in part, the following reasons: A new 3D ultrasound technology should provide the convenience of a hand-held scan head, should yield real-time 3D images, and should provide 2D images with quality equal to, or greater than, presently available 2D ultrasound images. Convenient size and a reasonable price are also requirements. In this paper, a 3D ultrasonic imaging method with the potential to meet the above criteria is described. It may also provide even higher quality 2D ultrasound images than are presently available. The new method relates more closely to computed tomography than to focused steered beams. It, however, uses projections and back-projections over 3D ellipsoids rather than straight lines; and it does this in a simple straight forward manner. Implementation in software of filtered ellipsoidal back-projection is described, resolution and side lobes are discussed, and examples of the 3D point image (re. point spread function) are given.