Image restoration by adaptive-neighborhood noise subtraction

A new algorithm for image restoration in the presence of additive white Gaussian noise is presented. This algorithm is based on a new, adaptive method to estimate the additive noise. The basic idea in this technique is to identify uniform structures or objects in the image by use of an adaptive neighborhood and to estimate the noise and the signal content in these areas separately. The noise is then subtracted selectively from the seed pixel of the adaptive neighborhood, and the process is repeated at every pixel in the image. The algorithm is compared with the adaptive two-dimensional least-mean-squares and the adaptive rectangular-window least-mean-squares algorithms for noise suppression. The results from the application of these algorithms to synthesized images and natural scenes are presented along with mean-squared-error measures. The new algorithm performs better than the other two methods both in terms of visual presentation and mean-squared error.     

神经网络识别图像椒盐噪声的自适应滤波方法

为了使椒盐噪声不影响图像的后续处理,提出一种基于BP神经网络噪声检测的自适应开关滤波器来检测和滤除图像椒盐噪声.该方法利用像素值及其邻域特性作为像素点的描述即神经网络的输入,通过神经网络自动检测图像的噪声位置,据此保持非噪声点不变,对噪声点进行自适应窗口大小的均值滤波处理,且仅窗口内非噪声点参与均值运算.实验结果表明,...     

General adaptive-neighborhood technique for improving synthetic aperture radar interferometric coherence estimation

A new method for filtering the coherence map issued from synthetic aperture radar (SAR) interferometric data is presented. For each pixel of the interferogram, an adaptive neighborhood is determined by a region-growing technique driven by the information provided by the amplitude images. Then pixels in the derived adaptive neighborhood are complex averaged to yield the filtered value of the coherence, after a phase-compensation step is performed. An extension of the algorithm is proposed for polarimetric interferometric SAR images. The proposed method has been applied to both European Remote Sensing (ERS) satellite SAR images and airborne high-resolution polarimetric interferometric SAR images. Both subjective and objective performance analysis, including coherence edge detection, shows that the proposed method provides better results than the standard phase-compensated fixed multilook filter and the Lee adaptive coherence filter.     

HSI空间和改进 C-means的彩色人民币号码分割方法

针对采集到的人民币号码图像都是彩色图像并携带有噪声这一现象,本文提出基于 HSI空间和改进的 C-means算法的人民币彩色号码图像分割方法。选用 HSI颜色空间作为彩色分割空间,在 HSI空间内,将 HSI的 3-D搜索问题转化为 3个 1-D的搜索问题,求取图像在 3个 1-D方向上的灰度直方图,该方法根据图像当前点 3×3邻域内每个像素灰度值与当前点灰度值差值的大小情况,确定聚类算法中当前点的灰度值 p(m)的值,采用 C-means聚类算法分别确定文字和非文字的聚类中心,利用欧式距离进行人民币号码前景和背景的聚类判断。该方法直接对彩色人民币号码图像进行分割,考虑了当前点与邻域像素点之间的相互关系,具有一定的自适应性。实验结果表明,提出的号码图像分割方法不受图像噪声和局部边缘变化的影响,且变换后数据量减少,易于计算,该方法对字母和数字的分割都有效,鲁棒性较强。     

基于自适应形态滤波的医学超声图像降噪

针对医学超声图像上的斑点噪声,本文提出一种基于自适应形态滤波的降噪方法.首先构造一组检测图像中不同像素值突变的结构因子;再对每个结构因子构造相应的形态滤波结构元;最后对每个像素点邻域进行结构检测,找到该点处最可能存在的突变结构,以相应的结构元完成该点的形态滤波.对不同信噪比的仿真图像和实际图像分别采用本文方法和各向异性扩散滤波,不同尺度传统形态滤波进行了:比较实验,结果表明:采用本方法可将超声图像的信噪比、对比度噪声比和图像优度分别平均提高15%、37%和69%,优于其它方法.     

采用自适应邻域马尔可夫场的极化SAR图像分割

提出了一种新的马尔可夫场(MRF)极化SAR图像分割方法,对于图像中的每个像素,利用极化SAR数据总功率(span)图,得到该像素的马尔可夫场自适应邻域系统,且对区域标号过程的参数进行修正.使用该方法对机载极化SAR数据进行分割,实验结果表明,与传统的马尔可夫场方法、最大似然方法相比,该方法可以得到较好的分割结果.     

Local frequency estimation for the fringe pattern with a spatial carrier: principle and applications

A local frequency estimation approach for the fringe pattern with a spatial carrier by which the 2D spatial frequencies at a certain pixel are estimated from its neighborhood is presented. The applications of this approach in the fringe pattern analyses are also introduced. First, a 2D spatial carrier phase-shifting algorithm is derived. With it the detuning errors induced by frequency mismatching are avoided, and the stronger phase deformations can be successfully coped with. Second, a novel aperture extrapolation method is developed by which the phase accuracies of the Fourier-transform method at the aperture boundaries are effectively improved.     

An adaptive method based on the improved LPA-ICI algorithm for MRI enhancement

Various diseases are diagnosed using medical imaging used for analysing internal anatomical structures. However, medical images are susceptible to noise introduced in both acquisition and transmission processes. We propose an adaptive data-driven image denoising algorithm based on an improvement of the intersection of confidence intervals (ICI), called relative ICI (RICI) algorithm. The 2D mask of the adaptive size and shape is calculated for each image pixel independently, and utilized in the design of the 2D local polynomial approximation (LPA) filters. Denoising performances, in terms of the PSNR, are compared to the original ICI-based method, as well as to the fixed sized filtering. The proposed adaptive RICI-based denoising outperformed the original ICI-based method by up to 1.32 dB, and the fixed size filtering by up to 6.48 dB. Furthermore, since the denoising of each image pixel is done locally and independently, the method is easy to parallelize.     

邻域自适应选取的局部投影非线性降噪方法

局部投影降噪算法已广泛应用于非线性时间序列的分析中，但受邻域选取的影响较大。提出了一种按照自适应方式选取邻域大小的局部投影降噪算法。首先用时间延迟方法将一维时间序列重构到高维相空间。然后逐步增大每个待分析相点的领域大小，根据领域最大主方向变化过程中首次出现平稳阶段时，自适应地确定该相点的最优领域，最后再用局部几何投影的方法去除噪声成分。对洛伦兹信号和杜芬信号分别添加不同噪声水平的高斯白噪声，对领域自适应选取的局部投影算法与标准局部投影算法的降噪效果进行了比较。实验结果表明，自适应邻域选取方法，提高了局部投影算法的降噪能力和对领域参数的鲁棒性。     

基于人眼视觉特性的邻域自适应模糊增强算法

针对灰度适中时人眼分辨力较强的视觉特性,利用Prewitt算子求得梯度图像,并在隶属函数的定义中引入像素的邻域均值分量,对梯度图像进行模糊域的自适应增强。实验证明该算法克服了传统模糊增强算法会对噪声点进行增强的缺点,在增强图像细节的同时有效地抑制了图像的噪声。     

Real-time adaptive image impulse noise suppression

In this paper, a new intelligent hardware module suitable for the computation of an adaptive median filter is presented for the first time. The function of the proposed circuit is to detect the existence of impulse noise in an image neighborhood and apply the operator of the median filter only when it is necessary. The noise detection procedure can be controlled so that a range of pixel values is considered as impulse noise. In this way, the blurring of the image in process is avoided, and the integrity of edge and detail information is preserved. Experimental results with real images demonstrate the improved performance. The proposed digital hardware structure is capable to process gray-scale images of 8-bit resolution and is fully pipelined, whereas parallel processing is used in order to minimize computational time. In the presented design, a 3/spl times/3 or 5/spl times/5 pixel image neighborhood can be selected for the computation of the filter output. However, the system can be easily expanded to accommodate windows of larger sizes. The proposed digital structure was designed, compiled and simulated using the MAX+PLUS II Programmable Logic Development System by Altera Corporation. For the implementation of the system the EPF10K200SRC240-1 field-programmable gate array device of the FLEX10KE device family is utilized, and it can be used in industrial imaging applications where fast processing is required. The typical clock frequency is 65 MHz.     

Designing multiplane computer-generated holograms with consideration of the pixel shape and the illumination wave

The majority of image-generating computer-generated holograms (CGHs) are calculated on a discrete numerical grid, whose spacing is defined by the desired pixel size. For single-plane CGHs the influence of the pixel shape and the illumination wave on the actual output distribution is minor and can be treated separately from the numerical calculation. We show that in the case of multiplane CGHs this influence is much more severe. We introduce a new method that takes the pixel shape into account during the design and derive conditions to retain an illumination-wave-independent behavior.     

New approach for enlargement of medical electronic endoscopic images

To compensate for the imperfections of the endoscopic mechanical structure and the limitations of working space, a new technology based on the recursive minimum/maximum method is proposed to enlarge images obtained by the medical electronic endoscope. This method can be used repeatedly to obtain image enlargement to 2x by optimizing the neighborhood information of the pixels of interest in adjustable windows. In order to ensure the best evaluation of the pixel, the algorithm criterion is presented to decide whether the new gray value is assigned to the pixel. Experimental results from enlarged endoscopic images are presented that demonstrate that the recursive minimum/maximum method for image enlargement can preserve the fine details with rich edge information and with better visualization.     

Robust and computationally efficient superresolution algorithm

Superresolution is the process of combining information from multiple subpixel-shifted low-resolution images to form a high-resolution image. It works quite well under ideal conditions but deteriorates rapidly with inaccuracies in motion estimates. We model the original high-resolution image as a Markov random field (MRF) with a discontinuity adaptive regularizer. Given the low-resolution observations, an estimate of the superresolved image is obtained by using the iterated conditional modes (ICM) algorithm, which maximizes the local posterior conditional probability sequentially. The proposed method not only preserves edges but also lends robustness to errors in the estimates of motion and blur parameters. We derive theoretically the neighborhood structure for the posterior distribution in the presence of warping, blurring, and downsampling operations and use this to effectively reduce the overall computations. Results are given on synthetic as well as real data to validate our method.     

An Adaptive Image Calibration Algorithm for Steganalysis

In this paper, a new adaptive calibration algorithm for image steganalysis is proposed. Steganography disturbs the dependence between neighboring pixels and decreases the neighborhood node degree. Firstly, we analyzed the effect of steganography on the neighborhood node degree of cover images. Then, the calibratable pixels are marked by the analysis of neighborhood node degree. Finally, the strong correlation calibration image is constructed by revising the calibratable pixels. Experimental results reveal that compared with secondary steganography the image calibration method significantly increased the detection accuracy for LSB matching steganography on low embedding ratio. The proposed method also has a better performance against spatial steganography.     

Two‐ and three‐dimensional transition element families for adaptive refinement analysis of elasticity problems

In this paper, new enhanced assumed strain (EAS) and hybrid stress transition element families are developed for 2D and 3D adaptive refinement analysis of elasticity problems. The EAS element families are based on some existing incompatible transition element families. By using the EAS method and the previous incompatible modes, the B ‐matrix columns associated with the EAS modes can be directly designed such that their domain integrals vanish automatically and they can be computed more efficiently. For 2D hybrid stress transition element families, it is possible to derive different stress fields that lead to rank‐sufficient transition elements. However, the task becomes intractable for 3D hybrid stress transition elements in which many combinations of mid‐side and mid‐face nodes are possible. This paper proposes to use hybrid stress transition element families in which the assumed stress fields are linearly complete. The new 2D element family is more accurate than the 2D rank‐sufficient element family. The new 3D element family is more accurate than the one with additional bilinear stress modes. Numerical examples reveal that the most accurate transition element families are the newly developed hybrid stress families followed by the EAS families, the incompatible families and then the compatible families. Copyright © 2008 John Wiley & Sons, Ltd.     

基于平滑卷积定位的圆形印鉴提取方法研究

利用圆形印鉴中心的五角星所在区域红色像素分布集中的特点,提出了一种基于平滑卷积定位的圆形印鉴提取算法.该算法首先将彩色票据图像转换为灰度图像,接着利用平滑卷积定位五角星区域中的一个像素点,以这个像素点邻域的平均灰度值作为阈值二值化票据图像,然后搜索圆形印鉴边框,计算圆心坐标和半径,从而实现印鉴的提取.同时,为了提高提取速度,通过适当减小卷积过程中图像的分辨率,优化了整个提取过程中时间复杂度最高的平滑卷积算法.实验结果表明,这种方法能够在复杂背景下有效地提取出圆形印鉴,在经过算法优化后,提取速度提高了近12倍.     

Algorithms for automated meshing and unit cell analysis of periodic composites with hierarchical tri‐quadratic tetrahedral elements

Unit cell homogenization techniques together with the finite element method are very effective for computing equivalent mechanical properties of composites and heterogeneous materials systems. For systems with very complicated material arrangements, traditional, manual mesh generation can be a considerable obstacle to usage of these techniques. This problem is addressed here by developing automated meshing techniques that start from a hierarchical quad‐tree (in 2D) or oc‐tree (in 3D) mesh of pixel or voxel elements. From the pixel/voxel mesh, algorithms are presented for successive element splitting and nodal shifting to arrive at final meshes that accurately capture both material arrangements and constituent volume fractions, and the material‐scale stress and strain fields within the composite under different modalities of loading. The performance and associated convergence behaviour of the proposed techniques are demonstrated on both densely packed fibre and particulate composites, and on 3D textile‐reinforced composites. Copyright © 2003 John Wiley Sons, Ltd.     

Moving object detection based on confidence factor and CSLBP features

Moving object detection is a challenging task in many computer vision applications. In this paper, we propose a robust background modelling method for this task. First, the background is updated by an adaptive strategy based on Centre-symmetric Local Binary Patterns. Then, background subtraction is used for detecting moving object. Although the traditional background subtraction technique uses the difference value between the current pixel and its corresponding background pixel for objection detection, our method utilises the confidence factor to determine whether the current pixel is a background or foreground pixel. The confidence factor of the current pixel is calculated in term of the difference values of its neighbourhood pixels. In the experiments, the proposed algorithm is tested on several challenging datasets such as PETS 2009, BMC 2012 and SABS. The experimental results demonstrate that our algorithm can robustly detect moving object under various scenes.     

Integral floating display systems for augmented reality

Novel integral floating three-dimensional (3D) display methods are proposed for implementing an augmented reality (AR) system. The 3D display for AR requires a long-range focus depth and a see-though property. A system that adopts a concave lens instead of a convex lens is proposed for realizing the integral floating system with a long working distance using a reduced pixel pitch of the elemental image. An investigation that reveals that the location of the central depth plane is restricted by the pixel pitch of the display device is presented. An optical see-through system using a convex half mirror is also proposed for providing 3D images with a proper accommodation response. The concepts of the proposed methods are explained and the validity of system is proved by the experimental results.