一种高精度的荧光单分子纳米级定位算法

荧光成像系统的技术指标、采集的荧光图像信噪比和单分子定位算法是影响单分子定位精度的3大因素.在介绍单分子定位的基本极限精度和理论计算精度的基础上,提出了一种被称为图像去噪高斯掩膜算法的单分子定位算法.依据实验用单分子成像系统的具体配置,通过计算机仿真表明,该算法良好的去噪处理和高斯加权质心运算方式,不仅能实现纳米级的定位精度,而且能突破一般理论计算精度的限制,接近基本极限精度,特别是在背景噪声较大的情况下,其优势更加明显.这对单分子的精确定位和跟踪、扩散方式分析、转移速率计算等具有重要的意义.     

A discrete-scatterer model for ultrasonic images of rough surfaces

Automated analysis of ultrasonic images could be greatly improved with model-based Bayesian methods for image analysis. Such an approach would require an accurate probabilistic image model representing ultrasonic images in terms of the gross shape of underlying anatomical structure. Existing probabilistic models for ultrasonic image data do not adequately incorporate structure shape or system characteristics; thus, a substantially new approach is warranted. Toward that goal, we have developed models for the imaging system and rough surface with the following objectives: (1) accuracy in representation of basic image characteristics such as the texture and intensity, (2) a minimum of computational requirements, and (3) a form that is naturally extendable to an appropriate probabilistic image model. The imaging system was modeled as a linear system with a separable three-dimensional point-spread function with an envelope of Gaussian curves in each dimension. The rough surface was modeled as a collection of discrete scatterers placed on the continuum and parametrized by a surface roughness and scatterer concentration. Models were evaluated by a visual comparison of actual and simulated images of a cadaveric lumbar vertebra. The gross shape of the vertebral surface was estimated from computed tomography images of the vertebra, and simulated images were generated using the models and the gross surface shape. Actual images were registered with the surface and simulated images to within 2 mm. The similarity of the actual and simulated images was quite remarkable considering the simplicity of the models. Differences between the images were less than those between two simulated images separated by 0.4 mm or one-fifth the registration error. Further assessment of the models would require a statistical approach not yet available. The models do, however, provide the basis for the development of a computationally tractable probabilistic image model for image analysis. Such a model will provide the means for a statistical evaluation of the system and surface models.     

小波去噪方法在管道应力波检测中的应用

介绍了一种适合于管道应力波检测的基于小波变换的去噪方法。利用小波变换多尺度分析的优点。根据有用信号和噪声在小波变换不同尺度下的传递特性的不同，进行小波系数阈值选取后，对剩余小波系数重建信号，得到有用信号的波形。结果表明，它能较好地抑制噪声，使信号的信噪比明显提高。     

多重约束下由粗到精的多源图像自适应配准算法

本文提出了一种多重约束下由粗到精的多源图像自适应子像素级配准算法.该算法采用影像特征点作为匹配基元,利用具有不同精度等级的组合判据法、整体松弛法、最小二乘法实现由粗到精的匹配,同时在匹配过程中加入了多重约束,如定位点控制约束、交叉匹配约束、连续控制约束,以保证获取的配准控制点的可靠性和剔除粗差点.此外,该算法利用配准控制点自适应地构建整个图像的三角网,最后依据改进的三角形填充算法对目标图像进行逐像点纠正.对同源和非同源的遥感图像的实验证明,SPOT4全色图像(10m/pixel)和SPOT5多光谱图像(10m/pixel)的配准精度分别达到6～7m和5～6m.     

高精度星敏感器星点光斑质心算法

高精度星敏感器星点光斑的质心精度是星敏感器整体精度的基础,它需要达到角秒级的量级。因此,提出了一种基于亚像元相关法的星像质心算法。这种算法是利用互相关匹配实现图像定位的原理,将星像质心定位到亚像素上来提高质心精度。它可以克服由于系统误差和图像采集所带来的误差。根据系统的光学参数设计以及星像的光谱、亮度及其在视场中的位置特征,仿真得到点列图模型,针对视场内与光轴的不同夹角仿真制作一系列亚像元理想模板,然后对星像加高斯随机噪声,把有随机噪声的星像与理想星像进行相关运算来求星像质心精度。通过仿真实验,得到相关法具有较高的星像质心精度,定位精度可以优于1/12个像素的量级。     

重采样和曲面拟合的图像匹配方法

模式识别中的目标匹配和定位是一个传统问题,但是大多数经典算法其定位精度都是象素级的.图像的亚象元匹配算法,可以突破物理分辨率的限制,把匹配和定位精度从象素级提高到亚象元级,从而满足大规模集成电路制造、摄影测量、工业检测和目标检测等应用对精度的要求.将重采样方法和曲面拟合法有机结合的图像亚象元匹配方法,既有重采样方法精度高的优势,同时通过曲面拟合法加快了计算速度,减少了所需时间.实验结果证明了这种基于重采样和曲面拟合的图像亚象元匹配算法的有效性.     

实用干涉合成孔径声纳复图像配准法

海底地貌测绘的最新技术是利用干涉合成孔径声纳(InSAS)进行三维立体成像,其信号处理的关键在于成像之后的图像配准、干涉成像等步骤。图像配准的精度直接影响相位图的质量,从而影响所求目标区域高度的准确性。在分析InSAS复图像数据特点的基础上给出一种实用的基于最大干涉频谱法的复图像配准方法,缩减了配准搜索范围,在一定程度上提高了配准速度和精度。利用该方法对湖试测得的湖底地貌数据进行配准,用复图像相干系数和干涉相位图的残余点数对配准效果进行评估,通过配准前后的参数比较,证实了最大干涉频谱法用于InSAS复图像配准能够取得较好的配准效果。     

脊波变换在眼底图像中的去噪效果评价

针对实际的眼底图像中含有噪声,严重影响对病灶的诊断,根据其先验知识,本文采用四种多尺度几何变换技术对其进行去噪处理,即脊波,加维纳滤波的脊波、小波和轮廓波算法;并给出基于高斯波形提取的LMLSD(局部均值和局部标准差)算法,估算处理后图像的SNR(信噪比),对这四种去噪算法的处理效果进行客观的量化评价.实验结果表明,图像经加维纳滤波的脊波去噪算法处理后,图像最为清晰,SNR提高最为明显,较原始图像提高约5.04倍,客观量化评价结果与主观视觉感受一致.     

基于PCNN区域分割的图像邻域去噪算法

针对小波图像去噪方法中使用的NeighShrink方法,本文提出了一种有效的保护图像边缘的图像去噪算法.主要改进了NeighShrink方法中固定的邻域范围,根据图像自身的性质,自适应分割成不同的邻域对图像进行去噪处理;并进一步结合小波层内相关性,对各个不规则邻域加上固定的窗口,选择了几何距离更为接近且在同一不规则邻域内的系数,以完善NeighShrink方法.该算法采取平稳小波对含噪图像进行分解,以保持相位不变性,并对低频子带利用脉冲耦合神经网络模型进行图像分割,按照一定的规则将性质相似的像素点相接,得到原图像分割后的信息.在处理过程中利用得到的分割信息对边缘予以保护.实验结果表明,该方法在降低了图像噪声的同时又尽可能地保留了图像的边缘信息,是一种有效的去噪方法.     

Fluorescence axial localization with nanometer accuracy and precision

We describe a new technique, standing wave axial nanometry (SWAN), to image the axial location of a single nanoscale fluorescent object with sub-nanometer accuracy and 3.7 nm precision. A standing wave, generated by positioning an atomic force microscope tip over a focused laser beam, is used to excite fluorescence; axial position is determined from the phase of the emission intensity. We use SWAN to measure the orientation of single DNA molecules of different lengths, grafted on surfaces with different functionalities.     

基于亚像素边缘的摄像机标定板特征提取算法

目的在视觉测量领域,摄像机的标定精度是最终测量精确度的决定性因素,为了提高标定板特征的提取精度,提出一种基于亚像素边缘的提取方法。方法针对圆点标定板,首先采集标定板图像,对图像进行处理,获取像素级别边缘,然后以边缘像素点为中心,取3×3的数字窗口计算梯度方向,在梯度方向上进行像素点灰度的双曲正切拟合,获取亚像素级别边缘,最后对亚像素边缘按照圆形进行拟合,求得圆心坐标。结果实验表明算法的分辨率达到0.03个像素,精度可达0.1个像素。结论该算法具有稳定可靠,精度高,运算速度快等特点,能够应用于图像拼接和分割,特征提取和摄像机标定等领域。     

Uniform precision ultrasound strain imaging

Ultrasound strain imaging is becoming increasingly popular as a way to measure stiffness variation in soft tissue. Almost all techniques involve the estimation of a field of relative displacements between measurements of tissue undergoing different deformations. These estimates are often high resolution, but some form of smoothing is required to increase the precision, either by direct filtering or as part of the gradient estimation process. Such methods generate uniform resolution images, but strain quality typically varies considerably within each image, hence a trade-off is necessary between increasing precision in the low-quality regions and reducing resolution in the high-quality regions. We introduce a smoothing technique, developed from the nonparametric regression literature, which can avoid this trade-off by generating uniform precision images. In such an image, high resolution is retained in areas of high strain quality but sacrificed for the sake of increased precision in low-quality areas. We contrast the algorithm with other methods on simulated, phantom, and clinical data, for both 2-D and 3-D strain imaging. We also show how the technique can be efficiently implemented at real-time rates with realistic parameters on modest hardware. Uniform precision nonparametric regression promises to be a useful tool in ultrasound strain imaging.     

基于角点检测的图像镶嵌算法

由于采用普通照相机拍摄的照片可能出现图像扭曲、交叠和倾斜,现有的图像镶嵌算法仍不能有效的进行处理,而且在这方面的研究也相对甚少.本文针对此问题,提出了一种适用于图像发生任意角度的旋转变换下仍可实现精确镶嵌的算法.即首先是采用Harris算子进行角点提取,使提取的精度达到亚像素级;然后根据这些角点信息建立图像间的角点对应关系,并由此得到投影变换矩阵;接下来采用图像变形技术,通过逆向映射重建发生空间变换的图像,由此得到的变形图像与源图像再进行无缝拼合.实验证明,该算法是有效的,具有较高的镶嵌精度.     

Raman microspectroscopy: a comparison of point, line, and wide-field imaging methodologies

Three different Raman microspectroscopic imaging methodologies using a single experimental configuration are compared; namely, point and line mapping, as representatives of serial imaging approaches, and direct or wide-field Raman imaging employing liquid-crystalline tunable filters are surveyed. Raman imaging data acquired with equivalent low-power 514.5-nm laser excitation and a cooled CCD camera are analyzed with respect to acquisition times, image quality, spatial resolution, intensity profiles along spatial coordinates, and spectral signal-to-noise ratios (SNRs). Point and line mapping techniques provide similar SNRs and reconstructed Raman images at spatial resolutions of approximately 1.1 microm. In contrast, higher spatial resolution is obtained by direct, global imaging (approximately 313 nm), allowing subtle morphological features on test samples to be resolved.     

Quantitative assessment of image quality enhancement due to unsharp-mask processing in x-ray fluoroscopy

Spatial unsharp-mask processing and its variants are commonly used in x-ray radiography to enhance image contrast. We investigated the effect of three unsharp-masking filter kernels of different sizes on the detection of an advanced guidewire tip in simulated x-ray fluoroscopy image sequences. To isolate the effect of visual temporal processing, we repeated the experiments on single images. Filter gains were selected so that all three kernels increased the contrast of a 0.018-in. (0.457-mm) guidewire by a factor of 2 but had different effects on image noise and signal profiles. There was no statistically significant effect of unsharp masking on human-observer performance in single images. However, all three kernels significantly improved average performance in image sequences, and the guidewire contrast required for detection was reduced by 32%-40%. A prewhitening channelized observer model predicted the disparity between sequences and single images and fitted measurements at different kernel sizes well. A nonprewhitening observer model did not. We conclude that unsharp masking is a simple and effective method of improving guidewire visualization in fluoroscopically guided interventional procedures and that quantitative image quality studies are essential for evaluation of image-processing techniques in sequences such as x-ray fluoroscopy.     

Image denoising algorithms based on fractional sincα with the covariance of fractional Gaussian fields

Image denoising has been considered as an essential image processing problem that is difficult to address. In this study, two image denoising algorithms based on fractional calculus operators are proposed. The first algorithm uses the convolution of covariance of fractional Gaussian fields with the fractional sinc_α (FS) (sinc function of order α). The second algorithm uses the convolution of covariance of fractional Gaussian fields with the fractional differential Heaviside function, which is the limit of FS. In the proposed algorithms, the given noisy image is processed in a blockwise manner. Each processed pixel is convolved with the mask windows on four directions. The final filtered image based on either FS or fractional differential Heaviside function (FDHS) can be obtained by determining the average magnitude of the four convolution test results for each filter mask windows. The outcomes are evaluated using visual perception and peak signal to noise ratio. Experiments prove the effectiveness of the proposed algorithms in removing Gaussian and Speckle noise. The proposed FS and FDHS achieved average PSNR of 28.88, 28.26?dB, respectively, for Gaussian noise. The improvements outperform those achieved with the use of Gaussian and Wiener filters.     

基于反向条纹投影的多投影显示系统几何校准

多投影器大屏幕显示系统的一项关键技术是如何实现多个投影器的精确校准。本文提出一种基于反向条纹投影原理的,简单、快速、高精度的校准方法。该方法通过投影正弦条纹测量屏幕相位分布,建立投影器和摄像机像素之间的几何传递关系,然后根据期望图像为每个投影器产生各自的投影图像。该方法仅需一部摄像机,并且无须对它或投影器进行标定,屏幕也无须是平面。实验结果表明,在摄像机方向观察可以得到几何校准良好的图像,校准精度可达到亚像素级。     

All-digital ring-wedge detector applied to image quality assessment

In the automatic assessment of image quality we obtained a high accuracy in the classification of image degradations in a manner that is widely independent of scene content. Using an all-digital ring-wedge detector system combined with neural-network software, we conducted several experiments in which the end goal is to classify images according to numerical quality scales. Experiments are presented to stress the importance of both local and global image quality assessment. Two databases of degraded images were prepared. One uses five levels of Gaussian blur to simulate depth of field. The other was prepared with lossy compression and recovery with artifacts generated by a JPEG (Joint Photographic Experts Group) compression algorithm. In quantitative terms our best sorting of Gaussian blur without knowledge of the original scene was to an accuracy of 96%. For degradation using JPEG we obtained an accuracy of 95% without knowledge of the original and 98% when the original scene is available as a reference.     

基于高斯积分曲线拟合的亚像素边缘提取算法

针对传统边缘提取算法定位精度低、对噪声敏感等缺点,提出一种基于高斯积分曲线拟合的亚像素边缘提取算法。通过曲面插值求取像素级边缘法截线上各离散点的灰度值,再进行高斯积分曲线拟合,寻找高斯积分曲线的均值点坐标,实现亚像素边缘的精定位。用量块直线边缘进行实验,并与现有亚像素边缘提取算法比较,实验证明基于高斯积分曲线拟合的亚像素边缘提取算法定位精度较高,可以达到1 μm,且算法可靠性高、计算速度快,能够用于高精度测量。     

Statistical algorithms for target detection in coherent active polarimetric images.

We address the problem of small-target detection with a polarimetric imager that provides orthogonal state contrast images. Such active systems allow one to measure the degree of polarization of the light backscattered by purely depolarizing isotropic materials. To be independent of the spatial nonuniformities of the illumination beam, small-target detection on the orthogonal state contrast image must be performed without using the image of backscattered intensity. We thus propose and develop a simple and efficient target detection algorithm based on a nonlinear pointwise transformation of the orthogonal state contrast image followed by a maximum-likelihood algorithm optimal for additive Gaussian perturbations. We demonstrate the efficiency of this suboptimal technique in comparison with the optimal one, which, however, assumes a priori knowledge about the scene that is not available in practice. We illustrate the performance of this approach on both simulated and real polarimetric images.