相干激光雷达图像散斑噪声抑制算法

提出了一种新的用于散斑噪声抑制的非线性加权均值多方向形态滤波算法。运用此算法和先前提出的散斑噪声抑制算法以及小波软阈值算法和Lee滤波算法一并对相干激光雷达图像进行了噪声抑制处理，并且对处理的结果进行了比较，证明了本算法的进步，即在不降低噪声抑制能力的前提下，较好地保持了图像边缘。     

数字全息技术中散斑噪声滤波算法比较

 在数字全息测量记录过程中,其所记录的全息图易受到散斑噪声的污染造成分辨率下降,同时也严重影响数字全息再现的效果,因此研究适用于数字全息技术中散斑滤波的算法具有重要的实用价值。介绍了中值滤波、Lee滤波、Kuan滤波和SUSAN滤波这四种常用的散斑滤波算法,并将它们运用于数字全息实验所记录图像和数字再现图像的散斑噪声滤波处理中,然后对这四种算法的处理结果进行评价。结果表明,在数字全息技术中使用SUSAN滤波算法进行处理,既明显抑制了散斑噪声,又有效保证了再现图像信息的完整性。     

基于改进旋滤波的电子散斑干涉图滤波方法

电子散斑干涉术条纹图在成像时不可避免地受散斑噪声调制,去除噪声是散斑干涉条纹处理的一项重要任务。利用散斑条纹图的方向性,提出一种基于模糊方向的旋滤波:在当前点的领域内定义4个模糊方向窗口,将传统旋滤波的一维、精确方向窗口的确定,转变为模糊方向窗口的确定;在确定的窗口内进行低通滤波时,采用自适应加权均值滤波代替传统的中值滤波。利用该方法分别处理模拟散斑条纹图和实验所得的真实条纹图,并与传统旋滤波、双边滤波和小波丢弃子带方法比较。实验结果表明,该改进算法在滤除散斑条纹图噪声的同时,有效保护了条纹的细节信息。     

散斑条纹图的自适应窗口滤波方法

针对散斑噪声很难用常用的滤波方法进行滤除,在已有等值线滤波方法的基础上,提出一种更优的自适应窗口滤波方法。由于等值线窗口是在条纹方向图的基础上得到的,深入研究条纹方向的求取方法,提出了一种更为可靠的条纹方向求取算法,在得到高精度条纹方向的同时,还能估计出条纹的密度。使用等值线窗口技术,保持了窗口形状的自适应能力,然后利用对条纹密度的估计,根据条纹的宽度来确定滤波窗口的大小,实现了滤波窗口大小的自适应。最后,根据条纹方向和滤波后的图像可以直接得到条纹密度变化较大的单幅散斑图的相位结果。     

电子散斑干涉条纹的计算机自动处理

电子散斑干涉条纹的噪声较强,一些常用的图像去噪、二值化、细化等算法对散斑干涉条纹的处理都存在一定的不足.针对散斑条纹的灰度值具有由两边向中间逐渐增强的特点,提出了一种新的计算机自动处理算法.该方法首先对干涉条纹进行巴特沃思滤波去噪、二值化,然后对其应用Hilditch细化计算机,实验结果表明此算法能较好地对一幅散斑干涉条纹图像进行细化.     

用电子散斑干涉法测微小角度

用电子散斑干涉法建立了微小角度定量测量系统,根据散斑噪声的特点,计算散斑图像沿不同方向的投影及投影的调制度,调制度最大值投影的周期为干涉条纹的宽度.实验结果表明该方法最小可测量角度为10-5 rad.     

散斑干涉相位条纹图的频域滤波处理

为了解决在数字散斑干涉技术测量时,散斑干涉相位条纹图像中大量噪声对相位解包裹结果和精度产生严重影响的问题,介绍了一种条纹正余弦分解和频域低通滤波结合的方法,实现了散斑干涉相位条纹图的高精度滤波。该方法的基本思路是在对相位图像进行滤波处理前,先将相位图通过正余弦函数进行映射转换成两幅图,分别经过频域滤波,然后再合成为相位图。这种分解频域滤波方法可以在滤波的同时,有效保留相位跳变信息。实验结果表明：与传统的图像降噪方法相比,该方法能够在保留图像“尖峰”信息的基础上,较好地滤除图像中的散斑噪声,方法简单有效,有效解决了传统滤波方法应用在相位条纹图中,相图灰度信息丢失10%~40%的问题。     

数字散斑条纹图的滤波方法

在现代数字散斑测量方法中，一般采用减模式来产生数字散斑条纹图，它是进一步图像处理的信息载体，同时不可避免地附带有大量的乘性噪声。为了保证测量精度，在进一步图像处理前必须对其进行降噪，选择合适的滤波方法显得尤为重要。在多年实际经验及阅读了大量文献的基础上，该文对国内外常用的数字散斑干涉条纹图滤波方法进行了分类阐述，选择了一些有代表性的方法予以实现，给出实验结果，并进行了对比分析。最后对数字散斑干涉条纹图滤波方法的发展方向给出了自己的看法。     

基于多分辨分析的合成孔径声纳相干斑抑制研究

相干斑噪声的存在使合成孔径声纳图像不能正确反映目标的反射特性,严重影响了图像的质量,降低了对图像的分析和理解性能。一个良好的合成孔径声纳图像相干斑抑制算法,必须在有效抑制相干斑噪声的同时,尽量保持图像中的边缘、点目标等细节信息。小波变换具有多分辨特性,可以利用其多分辨特性进行图像噪声消除。由于合成孔径声纳图像相干斑具有乘性噪声的性质,这就需要对其合成孔径声纳图像进行对数变换,把乘性噪声转换成加性噪声。然后对加性噪声进行小波多分辨分析和阈值处理,剔除小于阈值的小波系数后进行逆小波变换和指数变换,从而获得抑制相干斑噪声后的新的合成孔径声纳图像。从相干斑抑制的结果可以看出,基于多分辨分析的相干斑噪声抑制算法能够有效降低合成孔径声纳图像中的相干斑噪声。     

基于Gabor滤波的散斑条纹图平滑方法

提出了一种基于伽博(Gabor)滤波的散斑条纹图平滑方法.通过加窗傅里叶运算提取散斑条纹图的条纹频率和条纹梯度方向,并利用它们确定具有频率和方向选择性的Gabor滤波器对散斑条纹图进行Gabor滤波.数值模拟和实验结果表明,该方法在滤除散斑噪声的同时能够有效的保留散斑条纹图的条纹结构,为从单幅散斑条纹图中进一步提取条纹相位场奠定了良好的基础.     

Speckle Noise Suppressing Based on a Generalized Parallel Weighted-Average Multidirectional Morphological Filtering Algorithm

In this paper, a generalized parallel weighted-average multidirectional morphological filtering algorithm is presented to suppressing speckle noise. Simulation shows the algorithm can not only effectively suppress speckle noise but also preserve the geometrical features of images. Through comparison, it is proved that the algorithm is superior to F. Sara algorithm.     

Speckle Noise Suppressing Based on a Generalized Parallel Weighted-Average Multidirectional Morphological Filtering Algorithm

1 IntroductionThe coherent-imaging systems, such as LR(Laser Radar) and SAR(SyntheticAPerture Radar), generate images by coherent processing of the scattering echOsignals, so they are highly susceptible to speckle not,.Lll. The presence of speckle noise' in the images reduces the resolution and the tenet-explaining ability of the images.Thus it brings about an impact on the applications of the images and the detect~abilityof LR and SAR. However, removing speckle noise is one of the mos…     

Speckle suppressing based on morphological filter and fuzzy logic

A novel morphological filtering algorithm is proposed for suppressing speckle noise in images. The algorithm employs directional morphological close-open and open-close operations, then computing the membership of the filtered versions' every pixel according to the designed fuzzy rule. The final filtered image is composed of all the pixels with corresponding maximal membership. The validity of the algorithm is demonstrated.     

Speckle reduction for medical ultrasound images with an expectation-maximization framework

In view of inherent speckle noise in medical images,a speckle reduction method was proposed based on an expectation-maximization(EM) framework.First,the real component of the in-phase/quadrature(I/Q) ultrasound image is extracted.Then,it is used to blindly estimate the point spread function(PSF) of the imaging system.Finally,based on the EM framework,an iterative algorithm alternating between the Wiener Filter and the anisotropic diffusion(AD) is exploited to produce despeckled images.The comparison experiment is carried out on both simulated and in vivo ultrasound images.It is shown that,with respect to the I/Q image,the proposed method averagely improves the speckle-signal-to-noise ratio(S-SNR) and the edge preservation index(β) of images by the factor of 1.94 and 7.52.Meanwhile,it averagely reduces the normalized mean-squared error(NMSE) by the factor of 3.95.The simulation and in vivo results indicates that the proposed method has a better overall performance than exited ones.     

Speckle reduction by selective spatial-domain mask in digital holography

An improved method of using a selective spatial-domain mask to reduce speckle noise in digital holography is proposed.The sub-holograms are obtained from the original hologram filtered by the binary masks including a shifting aperture for being reconstructed. Normally, the speckle patterns of these sub-reconstructed images are different. The speckle intensity of the final reconstructed image is suppressed by averaging the favorable sub-reconstructed images which are selected based on the most optimal pixel intensity sub-range in the sub-holograms. Compared with the conventional spatial-domain mask method, the proposed method not only reduces the speckle noise more effectively with fewer sub-reconstructed images,but also reduces the redundant information used in the reconstruction process.     

Speckle interferometry for measurement of continuous deformations

Improvements of a method for measurement of continuous displacements and deformations with digital phase shifting speckle pattern interferometry are presented. The method is based on an algorithm that, with the knowledge of the initial phase, only needs one image at a time to evaluate continuos phase changes due to object deformations. In the improved method, the initial random phase of the speckle pattern is evaluated using a number of phase-shifted images before the deformation under study. This is used for increasing the accuracy of the initial phase estimation and reducing influences from image noise and other measurement disturbances. The phase-shifted speckle patterns are used as references for comparison with the speckle patterns of the deformed object, thereby increasing the reliability and accuracy of the phase estimations of the deformed patterns. The technique can be used for measuring deformations such as transients and other dynamic events, heat expansion as well as other phenomena where it is difficult to accomplish phase shifting during deformation.     

Speckle noise reduction by the composition of diffused Fraunhofer holograms

The image reconstructed from a composite hologram is compared with that obtained by multiple-exposure of images independently reconstructed from a single element and also with that from a synthetic-aperture hologram. The experimental results show the difference in the principle of speckle noise reduction with these three methods and prove that the composite hologram arranged only in a row is sufficient for reducing the speckle noise.