An approach to suppress speckle noise and enhance edge

Anisotropic diffusion has good effect on reducing noise and preserving edge, but it may lose some details due to the blocky effect and can not suppress speckle effectively. The Laplacian factor is used to process the observed image which is considered as a piecewise planar image, so the Fourth Order Anisotropic Diffusion （FOAD） can avoid the blocky effect. The edge is preserved and enhanced by the Line Edge Detector （LED） based on stick technique and hypothesis test optimizing method. An approach called the Fourth Order Anisotropic Diffusion and Edge Enhancing （FOADEE）, where the LED is combined with the FOAD, is presented. For quantitative evaluation and comparison with the LED, the FOAD and the FOADEE, two parameters as measure of the noise suppression and edge preservation are introduced. It is proved that the novel method can not only suppress speckle prominently but also preserve even enhance edge and useful details effectively by applying it to the phantoms and tissue images.     

Nonlinear multiscale wavelet diffusion for speckle suppression and edge enhancement in ultrasound images

This paper introduces a novel nonlinear multiscale wavelet diffusion method for ultrasound speckle suppression and edge enhancement. This method is designed to utilize the favorable denoising properties of two frequently used techniques: the sparsity and multiresolution properties of the wavelet, and the iterative edge enhancement feature of nonlinear diffusion. With fully exploited knowledge of speckle image models, the edges of images are detected using normalized wavelet modulus. Relying on this feature, both the envelope-detected speckle image and the log-compressed ultrasonic image can be directly processed by the algorithm without need for additional preprocessing. Speckle is suppressed by employing the iterative multiscale diffusion on the wavelet coefficients. With a tuning diffusion threshold strategy, the proposed method can improve the image quality for both visualization and auto-segmentation applications. We validate our method using synthetic speckle images and real ultrasonic images. Performance improvement over other despeckling filters is quantified in terms of noise suppression and edge preservation indices.     

基于Nakagami分布的自适应斑点抑制与边缘增强方法

超声图像中的特殊斑点噪声严重影响了图像质量,针对此问题提出了一种基于Nakagami分布的自适应斑点抑制与边缘增强方法.根据斑点噪声的Nakagami分布模型,设计一个基于斑点局部统计特性的自适应滤波器.并应用"窄条"技术以不同方向与长度的"窄条"来近似图像的局部线性特性,滤波区域采用"窄条"代替常用的方形窗口,其中"窄条"的方向由假设试验优化方法确定,"窄条"长度与斑点的局部统计特性相关.实验证明,该方法在抑制斑点噪声、保留与增强图像边缘和细节方面均具有良好的性能.     

A STATISTICAL NOISE MODEL AND MATHEMATICAL MODEL OF SPECKLE PATTERN AND ADAPTIVE FILTERING APPROACH

A statistical noise model and a mathematical model for real speckle pattern are presented in this paper, and then, in view of the models, a new adaptive suboptimal image filtering approach is proposed. The proposed approach, with the local direction features of speckle pattern, combines the characteristics of optimal linear filter with non-linear filter and is an adaptive approximation to linear minimum mean square error filter. Experimental results show that the proposed approach has fairly good edge-preserved performance, compared with other present image filters, as well as much better filtering performance and robustness for speckle pattern.     

一种基于自适应双向扩散过程的无源毫米波图像去噪与增强

研究和设计了一种新型自适应双向扩散过程,对无源毫米波图像进行降噪和增强处理.根据图像的局部特征进行自适应扩散处理,在图像的同质区域进行各向同性扩散降低噪声,在图像的边缘处沿着图像边缘的切向方向进行正向扩散降低噪声,沿着图像边缘的法向方向进行反向扩散锐化边缘.通过对仿真图像和实测的91.5 GHz无源毫米波图像的实验表明...     

扩频系统中最优干扰抑制技术研究——盲自适应算法及并行实现

为解决扩频系统在动态环境下的干扰抑制问题,分析了从最小均方误差(MMSE)准则和约束最小均值输出能量(MMOE)准则导出的递推最小二乘(RLS)算法和盲递推最小二乘(BRLS)算法的性能。采用正交三角分解克服两算法数值稳定性差,运算量大,很难并行实现的缺点,讨论了正交三角分解——递推最小二乘(QR-RLS)算法与正交三角分解——盲递推最小二乘(QR-BRLS)算法的配合使用,并给出实现QR-RLS算法和QR-BRLS算法的脉动阵列(systolic array)。理论分析和仿真结果均表明QR-RLS与QR-BRLS算法的合理配合能较好的解决动态环境下的干扰抑制问题。     

An adaptive calibration and beamforming technique for a GEO satellite data relay

High throughput data links from low Earth orbit satellites through a geostationary orbit satellite data relay have been proposed to increase the available contact times to ground stations. Accurate antenna beam pointing and tracking of moving targets are key requirements for the relay satellite. In this work, we propose an adaptive calibration and beamforming methodology on the basis of least mean squares, which is suitable for a geostationary orbit data relay. The target system consists of the combination of a high gain reflector fed by a digitally steerable patch antenna array. The proposed method is first presented by numerical cosimulation of the antenna and the calibration algorithm. The results are then validated in an outdoor experimental setup with all digital signal processing implemented in a field‐programmable gate array. We demonstrate the tracking ability and pointing performance of the digitally enhanced reflector antenna with gain fluctuations smaller than 3 dB over a field of view of at least 2,5°. The demonstrated performance shows that the digitally enhanced reflector antenna is a suitable candidate for long‐distance space communications.     

An approximate analytical framework for performance analysis of equal gain combining technique over independent Nakagami,Rician and Weibull fading channels

In this paper, an approximate analytical method for performance analysis of equal gain combiner (EGC) receiver over independent Nakagami and Rician fading channels is presented. We use a convergent infinite series approach which makes it possible to describe the probability of error of EGC receiver in the form of an infinite series. In this paper, we develop a new approximation method for computation of the required coefficients in this series which lets us to derive simple analytical closed-form expressions with good accuracy compared with the exact results existing in the literatures. Our proposed approximation method only needs the mean and the variance of the fading envelope, which are known for various fading distributions, and hence, bypasses the required integration over the fading envelope distribution while computing the required coefficients. This feature lets us to extend our approximation method for performance analysis of EGC receiver over independent Weibull fading channels where the required integration has not any closed-form or tabulated solutions. To give an application of our developed method, we analyze the probability of error of an EGC receiver for binary, coherent PSK (CPSK) modulation over independent Nakagami, Rician and weibull fading channels and study the effect of the fading conditions on the system performance.     

Optimal waveform design for generalized likelihood ratio and adaptive matched filter detectors using a diversely polarized antenna

In this paper, we address the performance optimization of adaptive detectors in Gaussian noise with unknown covariance matrix, based on a diversely polarized antenna (DPA). First, a general signal model is presented, where the system response is related to the characteristics of its transmitted pulses. Two adaptive detectors, i.e., generalized likelihood ratio and adaptive matched filter, are then adopted, and their expressions for the probabilities of false alarm and detection are provided. In particular, a waveform design algorithm to enhance the detection performance of both the detectors is proposed. Finally, simulation results illustrate the performance gain obtained with the proposed waveform design algorithm, i.e., by optimally selecting the polarization of the transmitted pulses of the DPA.     

一种基于统计特征的孤立点和边缘点检测算法

提出一种基于统计分布特征的图像孤立点和边缘点检测的方法。通过定义离群半径,将每个像素点的邻域点进行初步分类,得到疑似孤立点,然后根据每一个点在不同邻域被划分为疑似孤立点的次数,计算该点的孤立置信度。根据孤立点和边缘点具有不同的邻域无关性的特性,从而可以用不同的孤立置信度阈值将两者分别检测出来。实验表明,文中的方法能够有效地检测孤立点和边缘点。     

Simple Detection Based on Soft‐Limiting for Binary Transmission in a Mixture of Generalized Normal‐Laplace Distributed Noise and Gaussian Noise

In this letter, a simplified suboptimum receiver based on soft‐limiting for the detection of binary antipodal signals in non‐Gaussian noise modeled as a generalized normal‐Laplace (GNL) distribution combined with Gaussian noise is presented. The suboptimum receiver has low computational complexity. Furthermore, when the number of diversity branches is small, its performance is very close to that of the Neyman‐Pearson optimum receiver based on the probability density function obtained by the Fourier inversion of the characteristic function of the GNL‐plus‐Gaussian distribution.