一种新的SAR图像相干斑抑制算法

针对经典局域统计自适应滤波器的窗口大小问题,提出了一种新的用于抑制合成孔径雷达图像相干斑噪声的滤波算法.基于SAR图像的统计特性,窗口大小根据区域特征自动调整,尽可能将窗口调整为包含同一均匀区域,从而在保持细节的同时尽最大可能地抑制斑点噪声.实验结果表明,本算法不仅有效抑制了SAR图像的相干斑,保持图像的边缘细节.而且有着良好的图像视觉效果.     

抑制SAR图像相干斑的迭代方向滤波算法

为保护SAR图像边缘特征并有效提高对乘性相干斑噪声的抑制性能,该文提出一种基于迭代方向滤波的抑制图像相干斑新算法。该算法先借助高斯-伽马平行窗估计出的比率边缘强度映射(ESM)与方向信息,自适应地控制各向异性高斯核(AGK),生成沿ESM方向分布的具有各向异性支撑区域的局域窗。然后将SAR图像多种局部统计参量联合作为衰减因子,形成与SAR图像区域分布特性相适应的负指数衰减型加权系数,进而将负指数衰减型加权系数与局域窗带方向的各向异性支撑区域结合形成局域加权的方向滤波。最后对SAR图像迭代地进行方向滤波即可实现带边缘保护的相干斑抑制。实验结果表明,与多种抑斑算法相比,该文算法在SAR图像抑斑与边缘保护方面均获得了更好的性能。     

AN ADAPTIVE SPECKLE SUPPRESSION AND EDGE ENHANCEMENT TECHNIQUE

Speckle degrades severely the quality of medical B-scan ultrasonic images, especially it blurs edges and details of images. An adaptive speckle suppression and edge enhancement method based on Nakagami distribution is presented. The statistics of log-compressed echo images is derived for Nakagami distribution, An adaptive filter based on local statistical property of speckle is designed. The stick technique that utilizes sticks with different sizes and various orientations is applied to locally approximate certain linear features of image. The local regionis a stick insted of a usual window, the orientation of sticks is decided by hypothesis test optimizing method and the length of sticks is obtained by region growing technique. Performance of the new method has been tested on the phantom and ultrasound images of pig muscle and echocardiographic. The results show that the technique effectively reduces the speckle noise while preserving and enhancing the tissue edge and resolvable details.     

自适应调节滤波强度的SAR图像非局部平均抑斑算法

为提升对SAR图像乘性相干斑的抑制水平与边缘保护性能,该文提出了一种可自适应调节滤波强度(AFS)的SAR图像非局部平均(NLM)抑斑新算法(AFS-NLM)。该算法利用Frost滤波图像计算的局部均值与方差来改善SAR图像场景参量的估计,形成了一种能更好刻画SAR图像同质区与边缘区的改进Kuan滤波系数。利用局部均值比与改进Kuan滤波系数分别作为新的相似性测量参量与自适应衰减因子,构建了一种更适应SAR图像乘性噪声特性的改进NLM滤波。利用偏平滑参数与偏边缘保护参数控制下的改进NLM滤波,分别替代经典Kuan滤波模型中的像素局部均值与自身灰度值作为加权项,并采用由改进Kuan滤波系数构建的自适应调节因子对二者进行加权平均,从而形成了一种可自适应调节滤波强度的加权滤波新模型。实验表明,该文算法与近期多种先进算法相比,具有更好的相干斑抑制与边缘保护性能。     

基于混合迭代滤波的SAR图像相干斑抑制

该文将变窗Lee滤波与自蛇扩散结合,提出了一种抑制SAR图像相干斑噪声的混合迭代滤波新算法,并给出了SAR图像噪声方差的一种有效估计方法。该算法首先估计SAR图像局部统计参量,进而通过改进的变窗Lee滤波对SAR图像进行平滑去噪,接着利用自蛇扩散去除Lee滤波难以平滑的孤立点噪声与边缘噪声。在Lee滤波与自蛇扩散的混合迭代中,Lee滤波的窗尺度随迭代次数的增加而增大,从而在保护SAR图像边缘细节的同时,同质区得到更好平滑。实验结果表明,与已有多种抑斑算法相比,该文算法在SAR图像抑斑与边缘保护方面均获得了更好的性能。     

基于AOS非线性扩散的SAR图像去噪研究

针对合成孔径雷达(SAR)图像的斑点噪声,介绍了一种基于非线性各向异性扩散的去噪方法,该方法经过加性算子分离(AOS)方案离散可以保证其扩散迭代过程中滤波结果的绝对稳定,并且利用其在消除噪声的同时锐化边界的特点,将之引入SAR图像的斑点噪声抑制问题当中.通过对一幅SAR图像的滤波处理,以及若干衡量滤波算法效果的评价指标,将其与传统的自适应局域统计滤波方法进行分析比较,并得出相关结论,从而证实了该研究提出的AOS非线性扩散滤波法(AOS ND法)抑制SAR图像相干斑的可行性和有效性.     

一种新的高分辨率SAR图像相干斑噪声抑制算法

提出了一种新的基于小波变换对高分辨率合成孔径雷达图像相干斑噪声抑制的算法。首先从SAR图像相干斑噪声产生的机理出发，论述了通过传统的滤波方法在抑制高分辨率SAR图像的相干斑噪声时，损失了大量的边缘信息和纹理细节而采用小波变换降噪的优越性和必要性；其次论述了在小波域中如何利用高频局部的统计特性和分解尺度大小来选取滤波窗口尺寸进行滤波；最后通过实验结果说明了该方法比采用传统的固定窗来实现对高分辨率SAR图像的降噪、保留边缘信息和纹理细节有着更好的性能。     

A multiplicative Nakagami speckle reduction algorithm for ultrasound images

Speckle noise of ultrasound images is of multiplicative nature which degrades the image quality in terms of resolution and contrast. While there exist a number of algorithms for reduction of multiplicative Rayleigh distributed random speckle noise, the low signal-to-noise ratio (SNR) issue of the multiplicative Rayleigh noise is still not adequately resolved. In this paper, a simple 2-dimensional (2D) local intensity smoothing method is presented which transforms the Rayleigh noise contaminated in ultrasound images to Nakagami distributed noise so as to improve the SNR of processed images. A 2D total variation regularized Nakagami speckle reduction algorithm is derived based on the maximum a posteriori estimation framework, which performs well in restoring piecewise-smooth reflectivity and preserving fine details of the image. The proposed algorithm is verified by a series of computer-simulated and real ultrasound image data. It is shown that the algorithm considerably improves the quality of ultrasound images and outperforms the Rayleigh noise based speckle reduction methods in terms of speckle SNR and contrast-to-noise ratio.     

基于CxImage库的SAR图像Speckle噪声抑制

合成孔径雷达图像的相干斑噪声抑制是SAR信息处理中的一个重要环节。经典的Speckle噪声抑制通常作为一个处理模块集成在软件中,但现有软件代码封装无法二次开发。针对文中提出了一种基于开源图像库CxImage的空间域自适应Speckle噪声抑制算法的应用与集成。将CxImage图像库链接入MFC应用程序框架中,利用其图像管理、维护、处理功能对SAR图像进行维护管理,集成多种经典的空间域自适应滤波方法,并以ERS-2卫星的PRI SAR数据为例,进行Speckle噪声滤波处理,选取适当的滤波效果评价参数,对滤波结果进行比较,最终得出各滤波算法应用于SAR图像滤波的优劣。     

SAR相干斑AWMAP抑制算法

MAP滤波器是一种常用的抑制SAR图像相干斑噪声的滤波器。针对SAR图像的特点提出了一种自适应窗口MAP算法（AWMAP），它根据窗内像素点的统计特征自适应调节窗口大小来增强噪声抑制性能。实际SAR图像处理表明，AWMAP算法在抑制噪声斑点和保留图像细节方面较原方法都有较大的改进和提高。     

A refined gamma MAP SAR speckle filter with improved geometricaladaptivity

A modified version of the refined gamma maximum-a-posteriori (RGMAP) speckle filter, which is found in the literature, is presented. The traditional RGMAP speckle filter first defects contours belonging to step edges and thin linear structures, then applies the RGMAP filter to local statistics extracted from rectangular masks that do not cross image contours. The proposed modified RGMAP (MRGMAP) filter first exploits local operators belonging to the odd-symmetric filter category employed by RGMAP to detect image segments, then it computes local statistics over areas that are not necessarily rectangular, but are subsets of the image segments having any possible shape. Therefore, MRGMAP enhances the RGMAP ability in exploiting shape adaptive windowing near image contours, where speckle is not fully developed. The MRGMAP computation time is estimated to be of the same magnitude of that of the original RGMAP, the latter depending on the number of filter categories being employed. The qualitative and quantitative results of the MRGMAP filter applied to real SAR images are satisfactory as the filter seems to be effective in speckle removal whereas it retains edge sharpness and subtle details. However, tests on simulated SAR images must still be performed in order to provide definitive evidence supporting MRGMAP effectiveness. Since MRGMAP typically removes image structures featuring a constant reflectivity gradient, this filter is not particularly suitable for image enhancement in human photo-interpretation. MRGMAP can be rather employed as a preprocessing module in a computer-based SAR image classification procedure based on segment mean value analysis     

融合局部和非局部信息的自适应贝叶斯分割方法

传统基于马尔可夫随机场(MRF)的贝叶斯分割方法由于只考虑邻域像素点的先验影响,无法有效抑制相干斑噪声;边缘区域分割效果欠佳,因为先验模型假定邻域中每个像素对中心像素的影响相同。因而,该文提出一种融合局部和非局部信息的自适应贝叶斯分割方法。针对SAR图像中的相干斑噪声模型,引入基于比率概率的相似性测度,用非局部相似像素块指导当前像素点的分割;并且采用变分系数(Coefficient of Variation, CV)方法获取边缘区域图像模板,在边缘区域自适应地调整定义的结构指数以及搜索窗尺寸,从而改善分割过度平滑与结构保持的矛盾;在实验分析中,利用新方法对部分图像进行了分割实验,并与传统方法作了比较。改进方法的分割结果形状更为准确,不但抑制了相干斑噪声,还有效保持了细节特征,具有显著优势。     

自适应SAR图像边缘检测算法

边缘检测是图像分析的基础,在对SAR图像进行边缘检测时,由于SAR图像存在很强的相干乘性斑点噪声,几乎没有一种方法既能有效地检测边缘又能排除斑点噪声的影响而不产生较多的虚假边缘,特别是在低视数SAR的情况下,该文指出了在低视数情况下应当如何对Touzi ratio边缘检测方法和最大似然(ML)边缘方法的检测窗口进行改进,在对SAR图像进行边缘检测时,引入了自适应窗口的方法,并将其应用到Touzi ratio边缘检测和最大似然 (ML)两个恒虚警边缘检测算法中,取得了很好的改进效果,引入自适应窗口的方法也适用于其它的SAR图像边缘检测算法。     

激光主动探测图像散斑自适应滤波抑制方法研究

激光主动照明成像具有作用距离远、系统分辨率高、可在低照度背景等复杂环境下获取目标图像等优点,但探测图像会受散斑噪声干扰.把高斯滤波、均值滤波和自适应滤波方法分别应用到仿真实验中进行散斑噪声抑制,实验表明:与高斯滤波和均值滤波相比,自适应滤波能有效抑制图像噪声,保留图像的边缘和细节信息.利用自适应滤波方法对获取的单帧和多帧累加平均的激光主动探测图像进行散斑抑制实验,使用散斑对比度进行定量分析,结果表明多帧短曝光图像累加平均可有效抑制图像的散斑噪声,自适应滤波可进一步降低图像的散斑噪声.     

SAR image despeckling using heavy-tailed Burr distribution

Multiplicative speckle noise diminishes the radiometric resolution of the synthetic aperture radar (SAR) images and all the coherent images. Speckle removal adds an extra value to an automated SAR image interpretation and analysis. In this paper, dual-tree complex wavelet-transform-based Bayesian method is proposed for despeckling the SAR images. In each subband, the reflectance and noise of the logarithmically transformed wavelet coefficients are modeled using heavy-tailed Burr and zero-mean Gaussian distributions. The closed-form expression for the shape parameter of Burr distribution is derived by employing the Mellin transform. The resultant complex-free quadratic maximum a posteriori solution with suitable shrinkage function yields despeckled SAR images. Extensive experiments are carried out using real SAR images as well as simulated images. The proposed method performs well in terms of equivalent number of looks with 3.5751 dB improvement in homogeneous region1 of Pipe river SAR image, edge preservation with 0.6158 improvement, peak signal to noise ratio of 51.3305 dB, and mean structural similarity index measure of 0.9397 at 0.05 noise variance for synthetically speckled image in comparison to the existing methods and takes averagely 2.3461 times less computing time. The proposed method provides a computationally efficient better speckle reduction in homogeneous regions while still preserving the edge.     

Adaptive median filters: new algorithms and results

Based on two types of image models corrupted by impulse noise, we propose two new algorithms for adaptive median filters. They have variable window size for removal of impulses while preserving sharpness. The first one, called the ranked-order based adaptive median filter (RAMF), is based on a test for the presence of impulses in the center pixel itself followed by a test for the presence of residual impulses in the median filter output. The second one, called the impulse size based adaptive median filter (SAMF), is based on the detection of the size of the impulse noise. It is shown that the RAMF is superior to the nonlinear mean L(p) filter in removing positive and negative impulses while simultaneously preserving sharpness; the SAMF is superior to Lin's (1988) adaptive scheme because it is simpler with better performance in removing the high density impulsive noise as well as nonimpulsive noise and in preserving the fine details. Simulations on standard images confirm that these algorithms are superior to standard median filters.     

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.     

SAR图像去噪的分数阶多尺度变分PDE模型及自适应算法

在合成孔径雷达(SAR)图像相干斑噪声抑制中,保持图像的边缘和纹理是非常重要的。该文首先利用分数阶导数和负指数Sobolev空间对图像进行建模,建立了分数阶多尺度变分偏微分方程(PDE)模型,然后给出了模型参数自适应选择方法,并在此基础上提出了区域、尺度自适应的去噪算法。数值实验表明,新方法能在去除噪声,抑制图像的 阶梯效应,保持图像的边缘、纹理细节几个方面取得较好的效果。     

基于无监督分类的多视极化SAR相干斑滤波

相干斑噪声是引起SAR图像降质的主要原因之一。多视极化白化滤波器(MPWF)是一种专门应用于多视极化SAR图像降噪的有效技术。其中,滤波器参数估计的精确度直接决定了其滤波性能的好坏。对此,该文提出了一种新的基于无监督分类的自适应窗算法。该算法以分类图像作为对象;在滑动矩形窗内以中心像素作为参照物,自动搜索与其同类的像素并用于MPWF参数估计。实验结果表明,与其他几种典型的算法相比,该法不仅有效地抑制了相干斑,而且对图像的纹理信息具有很好的保持能力。     

Speckle noise reduction of medical ultrasound images in complex wavelet domain using mixture priors

Speckle noise is an inherent nature of ultrasound images, which may have negative effect on image interpretation and diagnostic tasks. In this paper, we propose several multiscale nonlinear thresholding methods for ultrasound speckle suppression. The wavelet coefficients of the logarithm of image are modeled as the sum of a noise-free component plus an independent noise. Assuming that the noise-free component has some local mixture distribution (MD), and the noise is either Gaussian or Rayleigh, we derive the minimum mean squared error (MMSE) and the averaged maximum ${a quad posteriori}$ (AMAP) estimators for noise reduction. We use Gaussian and Laplacian MD for each noise-free wavelet coefficient to characterize their heavy-tailed property. Since we estimate the parameters of the MD using the expectation maximization (EM) algorithm and local neighbors, the proposed MD incorporates some information about the intrascale dependency of the wavelet coefficients. To evaluate our spatially adaptive despeckling methods, we use both real medical ultrasound and synthetically introduced speckle images for speckle suppression. The simulation results show that our method outperforms several recently and the state-of-the-art techniques qualitatively and quantitatively.