An improved adaptive detail enhancement algorithm for infrared images based on guided image filter

Detail enhancement algorithms are important for raw infrared images to improve their overall contrast and highlight important information in them. To solve the problems that current algorithms like GF&DDE have, an improved adaptive detail enhancement algorithm for infrared images based on a guided image filter is proposed in this paper. It chooses the threshold for the base layer image adaptively according to the histogram statistical information and adjusts the mapping range of the histograms according to the dynamic range of the image. Besides, the detail layer is handled by a simpler adaptive gain control method to achieve the good detail enhancement effect. Finally, the base layer and the detail are merged according to the approximate proportion of the background and the details. Experimental results show that the proposed algorithm can adaptively and efficiently enhance different dynamic range images in different scenarios. Moreover, this algorithm has high real-time performance.     

GPU-based beamformer: fast realization of plane wave compounding and synthetic aperture imaging

Although they show potential to improve ultrasound image quality, plane wave (PW) compounding and synthetic aperture (SA) imaging are computationally demanding and are known to be challenging to implement in real-time. In this work, we have developed a novel beamformer architecture with the real-time parallel processing capacity needed to enable fast realization of PW compounding and SA imaging. The beamformer hardware comprises an array of graphics processing units (GPUs) that are hosted within the same computer workstation. Their parallel computational resources are controlled by a pixel-based software processor that includes the operations of analytic signal conversion, delay-and-sum beamforming, and recursive compounding as required to generate images from the channel-domain data samples acquired using PW compounding and SA imaging principles. When using two GTX-480 GPUs for beamforming and one GTX-470 GPU for recursive compounding, the beamformer can compute compounded 512 x 255 pixel PW and SA images at throughputs of over 4700 fps and 3000 fps, respectively, for imaging depths of 5 cm and 15 cm (32 receive channels, 40 MHz sampling rate). Its processing capacity can be further increased if additional GPUs or more advanced models of GPU are used.     

Parallel processing techniques for the speckle brightness phase aberration correction algorithm

The speckle brightness adaptive algorithm has previously been implemented in approximately real-time on low frequency, one-dimensional arrays. To increase the speed of this technique, a temporally parallel algorithm and a spatially parallel algorithm are described. Theoretical analyses, simulation results and experimental measurements are presented for these algorithms. Theoretical predictions indicate that these techniques increase the correction speed, but some decrease in the accuracy of the compensating phase estimate occurs. Simulation results indicate that these parallel algorithms perform well at removing the effects of phase aberration. Preliminary experimental measurements demonstrate the correction speed improvements achievable with these algorithms.     

Beaconless stochastic parallel gradient descent laser beam control: numerical experiments

We apply a target-in-the-loop strategy to the case of adaptive optics beam control in the presence of strong atmospheric turbulence for air-to-ground directed energy laser applications. Using numerical simulations we show that in the absence of a cooperative beacon to probe the atmosphere it is possible to extract information suitable for effective beam control from images of the speckled and strongly turbulence degraded intensity distribution of the laser energy at the target. We use a closed-loop, single-deformable-mirror adaptive optics system driven by a target-in-the-loop stochastic parallel gradient descent optimization algorithm minimizing a mean-radius performance metric defined on the image of the laser beam intensity distribution formed at the receiver. We show that a relatively low order 25-channel zonal adaptive optical beam control system controlled in this way is capable of achieving a high degree of turbulence compensation with respect to energy concentration if the tilt can be corrected separately.     

基于FPGA的线阵CCD雨滴图像快速连续识别方法

雨滴粒子直径和速度实时测量是雨滴谱参数计算的关键,为了实时、连续得到精确、可靠的统计雨滴样本数据,采用基于高速线阵CCD的光阵排列法对雨滴速度和直径进行非接触测量,通过FPGA构造雨滴图像乒乓操作缓存单元,存储两行连续一维动态雨滴图像,发挥FPGA的并行运算能力,利用FPGA快速实现雨滴动态图像连通域检测及连通域标记算法,进而实现雨滴粒子的直径和速度检测.实验证明,该方法能自动连续测量记录雨滴数量、粒径大小和收尾速度,为雨滴谱参数计算提供可靠样本数据.     

Benefits of Minimum-Variance Beamforming in Medical Ultrasound Imaging

Recently, significant improvement in image resolution has been demonstrated by applying adaptive beamforming to medical ultrasound imaging. In this paper, we have used the minimum-variance beamformer to show how the low sidelobe levels and narrow beamwidth of adaptive methods can be used, not only to increase resolution, but also to enhance imaging in several ways. By using a minimum-variance beamformer instead of delay-and-sum on reception, reduced aperture, higher frame rates, or increased depth of penetration can be achieved without sacrificing image quality. We demonstrate comparable resolution on images of wire targets and a cyst phantom obtained with a 96-element, 18.5-mm transducer using delay-and-sum, and a 48-element, 9.25-mm transducer using minimum variance. To increase frame rate, fewer and wider transmit beams in combination with several parallel receive beams may be used. We show comparable resolution to delay-and-sum using minimum variance, 1/4th of the number of transmit beams and 4 parallel receive beams, potentially increasing the frame rate by 4. Finally, we show that by lowering the frequency of the transmitted beam and beamforming the received data with the minimum variance beamformer, increased depth of penetration is achieved without sacrificing lateral resolution.     

电视制导序列图像快速分割及目标特征提取

针对电视制导系统需从包含多个干扰目标的序列图像中快速识别和跟踪导弹目标的要求,提出了一种基于二值图像索引图的序列图像快速分割及目标特征提取算法,在序列图像二值化后,只需由FPGA对其遍历一次就可得到一张含有目标信息的索引图表,再由DSP对该索引图表边遍历边计算就可得到图像所含目标的数量.面积,质心坐标,二阶矩不变量等特征.实验结果表明,该算法并行处理效率高,实时性好,完全可满足电视制导系统的要求.     

Improved fingerprint identification with supervised filtering enhancement

An important step in the fingerprint identification system is the reliable extraction of distinct features from fingerprint images. Identification performance is directly related to the enhancement of fingerprint images during or after the enrollment phase. Among the various enhancement algorithms, artificial-intelligence-based feature-extraction techniques are attractive owing to their adaptive learning properties. We present a new supervised filtering technique that is based on a dynamic neural-network approach to develop a robust fingerprint enhancement algorithm. For pattern matching, a joint transform correlation (JTC) algorithm has been incorporated that offers high processing speed for real-time applications. Because the fringe-adjusted JTC algorithm has been found to yield a significantly better correlation output compared with alternate JTCs, we used this algorithm for the identification process. Test results are presented to verify the effectiveness of the proposed algorithm.     

Fast Scene Reconstruction Based on Improved SLAM

Simultaneous location and mapping (SLAM) plays the crucial role in VR/AR application, autonomous robotics navigation, UAV remote control, etc. The traditional SLAM is not good at handle the data acquired by camera with fast movement or severe jittering, and the efficiency need to be improved. The paper proposes an improved SLAM algorithm, which mainly improves the real-time performance of classical SLAM algorithm, applies KDtree for efficient organizing feature points, and accelerates the feature points correspondence building. Moreover, the background map reconstruction thread is optimized, the SLAM parallel computation ability is increased. The color images experiments demonstrate that the improved SLAM algorithm holds better real-time performance than the classical SLAM.     

Parallel integral projection transform for straight electrode localization in 3-D ultrasound images

In surgical practice, small metallic instruments are frequently used to perform various tasks inside the human body. We address the problem of their accurate localization in the tissue. Recent experiments using medical ultrasound have shown that this modality is suitable for real-time visualization of anatomical structures as well as the position of surgical instruments. We propose an image-processing algorithm that permits automatic estimation of the position of a line-segment-shaped object. This method was applied to the localization of a thin metallic electrode in biological tissue. We show that the electrode axis can be found through maximizing the parallel integral projection transform that is a form of the Radon transform. To accelerate this step, hierarchical mesh-grid algorithm is implemented. Once the axis position is known, localization of the electrode tip is performed. The method was tested on simulated images, on ultrasound images of a tissue mimicking phantom containing a metallic electrode, and on real ultrasound images from breast biopsy. The results indicate that the algorithm is robust with respect to variations in electrode position and speckle noise. Localization accuracy is of the order of hundreds of micrometers and is comparable to the ultrasound system axial resolution.     

自适应并行遗传算法及其应用研究

本文首先分析遗传算法中杂交率和突变率对算法收敛的影响,提出了自适应并行遗传算法,然后研究了该遗传算法对神经网络同时进行网络结构和连接权值的优化问题,最后将自适应并行遗传算法应用于故障诊断网络的权值学习。     

Blocked element compensation in phased array imaging

In clinical applications using large apertures, a significant number of phased array elements may be blocked due to discontinuous acoustic windows into the body. These blocked elements produce undesired beamforming artifacts, degrading spatial and contrast resolution. To minimize these artifacts, an algorithm using multiple receive beams and the total-least-squares method is proposed. Simulations and experimental results show that this algorithm can effectively reduce imperfections in the point spread function of the imager. Combined with first-and second-order scatterer statistics derived from multiple receive beams, the algorithm is modified for blocked element compensation on distributed scattering sources. Results also indicate that compensated images are comparable to full array images, and that even full array images can be improved by removing undesired sidelobe contributions. This method, therefore, can enhance detection of low contrast lesions using large phased-array apertures.     

A parallel tracking method for acoustic radiation force impulse imaging

Radiation force-based techniques have been developed by several groups for imaging the mechanical properties of tissue. Acoustic Radiation Force Impulse (ARFI) imaging is one such method that uses commercially available scanners to generate localized radiation forces in tissue. The response of the tissue to the radiation force is determined using conventional B-mode imaging pulses to track micron-scale displacements in tissue. Current research in ARFI imaging is focused on producing real-time images of tissue displacements and related mechanical properties. Obstacles to producing a real-time ARFI imaging modality include data acquisition, processing power, data transfer rates, heating of the transducer, and patient safety concerns. We propose a parallel receive beamforming technique to reduce transducer heating and patient acoustic exposure, and to facilitate data acquisition for real-time ARFI imaging. Custom beam sequencing was used with a commercially available scanner to track tissue displacements with parallel-receive beamforming in tissue-mimicking phantoms. Using simulations, the effects of material properties on parallel tracking are observed. Transducer and tissue heating for parallel tracking are compared to standard ARFI beam sequencing. The effects of tracking beam position and size of the tracked region are also discussed in relation to the size and temporal response of the region of applied force, and the impact on ARFI image contrast and signal-to-noise ratio are quantified.     

EM algorithm‐based adaptive custom thresholding for image denoising in wavelet domain

In this article, a novel denoising technique based on custom thresholding operating in the wavelet transform domain is proposed. The denoising process is spatially adaptive and also sub‐band adaptive. To render the denoising algorithm space adaptive, a Vector Quantization (VQ)‐based algorithm is used. The design of the VQ is based on Expectation Maximization (EM) algorithm. The results of the algorithm is demonstrated on SAR images corrupted by speckle noise. Experimental results show that Custom thresholding function outperforms the traditional soft, hard, and Bayes threshoding functions, improving the denoised results significantly in terms of Peak Signal to Noise Ratio (PSNR). © 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 175–178, 2009     

一种自适应逆控制管道有源消声系统及其实现

在前馈有源噪声控制中，由于次级通道传递函数往往是非最小相位系统，直接使用传统的FXLMS算法时，导致系统的性能下降。提出一种基于NMP逆控制的自适应前馈有源噪声控制FXLMS算法，在电机、风机、通风管道系统上进行实时ANC实验，结果表明较传统的前馈FXLMS算法ANC系统消声性能有明显的改进。     

Image Averaging Using a Modified LMS Adaptive Algorithm

Abstract

In a previous paper [5], a new two-dimensional LMS(TDLMS) algorithm has been proposed for image averaging. The algorithm improved results over direct averaging without the need for any image alignment or any correlation operation. In this paper, we propose a more simplified adaptive LMS algorithm for image averaging, where the averaging process results in fewer computations. Also, the increase in computations, as a result of the increase in relative shift between input images, is now proportional to N where previously it was proportional to N ², N being the filter window dimension. The results presented in this paper compare the two methods as well as the direct averaging method. The results show that the simplification does not affect the output result greatly and that the adaptive averager compensates for the relative shift between images in the same way as the TDLMS adaptive averager.     

Synthetic receive aperture imaging with phase correction for motion and for tissue inhomogeneities. I. Basic principles

The use of a synthetic receive aperture (SRA) system to increase the resolution, of a phased-array imaging system severalfold, by utilizing the available number of parallel receiver channels to address a larger number of transducer elements through a multiplexer system, is considered. Recent studies indicate that transducers with a very large number of elements will improve the detectability of small or low contrast targets when adaptive focusing is used to compensate for the effects of acoustic velocity inhomogeneities in tissue. With the effectively increased transducer element count afforded by an SRA system, a 1-by-N phased array could be split into an M-by-N array in order to improve resolution in the elevation dimension. Simulation results illustrate the lateral resolution achievable with several types of imaging systems: SRA, synthetic focus, and conventional phased array. Simulated images demonstrate the improvement in contrast resolution achievable using SRA. Experimental results show the improvement in beam width achieved by an experimental SRA system.     

Iterative coupling algorithms for large multidomain problems with the boundary element method

A new parallel Robin-Robin adaptive iterative coupling algorithm with dynamic relaxation parameters is proposed for the boundary element method (BEM), and relaxation parameters are derived for other existing iterative coupling algorithms. The performances of the new algorithm and of the modified existing algorithms are investigated in terms of convergence properties with respect to the number of subdomains, mesh density, interface mesh conformity, and BEM element types. Results show that the number of subdomains and the refinement level of the mesh are the two dominant factors affecting the performances of the considered algorithms. The proposed parallel Robin-Robin algorithm shows the best overall convergence behavior for the tested large problems, thanks to its effectiveness in handling complex boundary conditions and large number of subdomains, thus resulting to be very promising for efficient parallel BEM computing and large coupling problems. Source code is available at https://github.com/BinWang0213/PyBEM2D .     

A parallel run‐time iterative load balancing algorithm for solution‐adaptive finite element meshes on hypercubes

Abstract

To efficiently execute a finite element program on a hypercube, we need to map nodes of the corresponding finite element graph to processors of a hypercube such that each processor has approximately the same amount of computational load and the communication among processors is minimized. If the number of nodes of a finite element graph will not be increased during the execution of a program, the mapping only needs to be performed once. However, if a finite element graph is solution‐adaptive, that is, the number of nodes will be increased discretely due to the refinement of some finite elements during the execution of a program, a run‐time load balancing algorithm has to be performed many times in order to balance the computational load of processors while keeping the communication cost as low as possible. In this paper, we propose a parallel iterative load balancing algorithm (ILB) to deal with the load imbalancing problem of a solution‐adaptive finite element program. The proposed algorithm has three properties. First, the algorithm is simple and easy to be implemented. Second, the execution of the algorithm is fast. Third, it guarantees that the computational load will be balanced after the execution of the algorithm. We have implemented the proposed algorithm along with two parallel mapping algorithms, parallel orthogonal recursive bisection (ORB) [19] and parallel recursive mincut bipartitioning (MC) [8], on a 16‐node NCUBE‐2. Three criteria, the execution time of load balancing algorithms, the computation time of an application program under different load balancing algorithms, and the total execution time of an application program (under several refinement phases) are used for performance evaluation. Experimental results show that (1) the execution time of ILB is very short compared to those of MC and ORB; (2) the mappings produced by ILB are better than those of ORB and MC; and (3) the speedups produced by ILB are better than those of ORB and MC.     

High-resolution retinal imaging with micro adaptive optics system

Based on the dynamic characteristics of human eye aberration, a microadaptive optics retina imaging system set is established for real-time wavefront measurement and correction. This paper analyzes the working principles of a 127-unit Hartmann-Shack wavefront sensor and a 37-channel micromachine membrane deformable mirror adopted in the system. The proposed system achieves wavefront reconstruction through the adaptive centroid detection method and the mode reconstruction algorithm of Zernike polynomials, so that human eye aberration can be measured accurately. Meanwhile, according to the adaptive optics aberration correction control model, a closed-loop iterative aberration correction algorithm based on Smith control is presented to realize efficient and real-time correction of human eye aberration with different characteristics, and characteristics of the time domain of the system are also optimized. According to the experiment results tested on a USAF 1951 standard resolution target and a living human retina (subject ZHY), the resolution of the system can reach 3.6?LP/mm, and the human eye wavefront aberration of 0.728λ (λ=785?nm) can be corrected to 0.081λ in root mean square (RMS) so as to achieve the diffraction limit (Strehl ratio is 0.866), then high-resolution retina images are obtained.