Image fusion scheme based on nonsubsampled contourlet and block-based cosine transform

A kind of nonsubsampled contourlet and block-based cosine transform (NSCBCT) is developed, and its application in image fusion is studied in this paper. The construction of filtering banks is based on the nonsubsampled contourlet transform (NSCT) and block-based discrete cosine transform (B-DCT). We combine NSCT and B-DCT to design filters that lead to NSCBCT with better singularity representation than either of them in isolation. A design framework based on the hybrid approach is proposed, which allows for the fast implementation based on NSCT and B-DCT respectively. In addition, a new image fusion scheme based on NSCBCT for multispectral and panchromatic satellite images is proposed. Firstly, because it adopts NSCT, the fused satellite images have higher spatial resolution than those based on wavelets. Secondly, based on the localized high frequency information provided by B-DCT, the proposed fusion scheme can reduce the spectral distortion of the fused image further. Experimental results show that the proposed fusion method is able to increase the spatial resolution and reduce the spectral distortion of the fused image at the same time.     

Wavelet-Based Hybrid Thresholding Method for Ultrasonic Liver Image Denoising

This paper presents a wavelet-based hybrid threshold method according to the soft- and hard-threshold functions proposed by Donoho. The wavelet-based hybrid threshold method may help doctors to know more details on the liver disease through denoising the ultrasound image of the liver. First of all, an analytical expression for the hybrid threshold function is discussed. The wavelet-based hybrid threshold method is then investigated for ultrasound image of the liver. Finally, we test the influence of this parameter on the proposed method with the real ultrasound image corrupted by speckle noise with different variances. Moreover, we compare the proposed method under the varying parameters with the soft-threshold function and the hard-threshold function. Three metrics, which are correlation coefficient, edge preservation index and structural similarity index, are measured to quantify the denoised results of ultrasound liver image. Experimental results demonstrate the potential of the proposed method for ultrasound liver image denosing.     

Fusion of remote sensing images based on nonsubsampled contourlet transform and region segmentation

The purpose of remote sensing images fusion is to produce a fused image that contains more clear, accurate and comprehensive information than any single image. A novel fusion method is proposed in this paper based on nonsubsampled contourlet transform (NSCT) and region segmentation. Firstly, the multispectral image is transformed to intensity-hue-saturation (IHS) system. Secondly, the panchromatic image and the component intensity of the multispectral image are decomposed by NSCT. Then the NSCT coefficients of high and low frequency subbands are fused by different rules, respectively. For the high frequency subbands, the fusion rules are also unalike in the smooth and edge regions. The two regions are segregated in the panchromatic image, and the segmentation is based on particle swarm optimization. Finally, the fusion image can be obtained by performing inverse NSCT and inverse IHS transform. The experimental results are evaluated by both subjective and objective criteria. It is shown that the proposed method can obtain superior results to others.     

Saliency motivated pulse coupled neural network for underwater laser image segmentation

The detection range of underwater laser imaging technology achieves 4—6 times of detection range of conventional camera in intervening water medium, which makes it very promising in oceanic research, deep sea exploration and robotic works. However, the special features in underwater laser images, such as speckle noise and non-uniform illumination, bring great difficulty for image segmentation. In this paper, a novel saliency motivated pulse coupled neural network(SM-PCNN) is proposed for underwater laser image segmentation. The pixel saliency is used as external stimulus of neurons. For improvement of convergence speed to optimal segmentation, a gradient descent method based on maximum two-dimensional Renyi entropy criterion is utilized to determine the dynamic threshold. On the basis of region contrast in each iteration step, the real object regions are effectively distinguished,and the robustness against speckle noise and non-uniform illumination is improved by region selection. The proposed method is compared with four other state-of-the-art methods which are watershed, fuzzy C-means, meanshift and normalized cut methods. Experimental results demonstrate the superiority of our proposed method to allow more accurate segmentation and higher robustness.     

Application of digital image correlation method to in-situ dynamic strain measurement

Application of digital image correlation (DIC) method to determination of in-situ dynamic strain is presented in this study. Firstly, an integrative software is programmed based on the DIC algorithms and point-wise least-squares fitting technique. Then, simulated speckle images are generated to study the computational accuracy of this software. The experimental setup and procedures for measuring in-situ dynamic strain through both DIC and strain gauge are proposed. The DIC results are close to those measured by strain gauge. This fact reveals that DIC is a practical and effective tool for in-situ dynamic strain measurement. Finally, the full-field in-situ dynamic strain of another specimen is measured by DIC, and the overall distribution of the strain in the measurement area is clearly shown.     

Infrared and visible image fusion based on region of interest detection and nonsubsampled contourlet transform

In order to enhance the contrast of the fused image and reduce the loss of fine details in the process of image fusion,a novel fusion algorithm of infrared and visible images is proposed.First of all,regions of interest(RoIs)are detected in two original images by using saliency map.Then,nonsubsampled contourlet transform(NSCT)on both the infrared image and the visible image is performed to get a low-frequency sub-band and a certain amount of high-frequency sub-bands.Subsequently,the coefcients of all sub-bands are classified into four categories based on the result of RoI detection:the region of interest in the low-frequency sub-band(LSRoI),the region of interest in the high-frequency sub-band(HSRoI),the region of non-interest in the low-frequency sub-band(LSNRoI)and the region of non-interest in the high-frequency sub-band(HSNRoI).Fusion rules are customized for each kind of coefcients and fused image is achieved by performing the inverse NSCT to the fused coefcients.Experimental results show that the fusion scheme proposed in this paper achieves better efect than the other fusion algorithms both in visual efect and quantitative metrics.     

一种散斑干涉条纹的细化处理

干涉条纹的细化可以减少数据存贮量、提高处理速度,同时最重要的是提高干涉条纹的判读精度.但由于散斑干涉条纹的信噪比较低,常用的图像分割算法对干涉条纹的二值化都会存在一部分失真,针对散斑干涉条纹的灰度级成规律分布的特点,提出一种不对其采用阈值分割即把干涉条纹二值化的算法,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.     

The Research on Infrared Image Denoising in Getting an Undistorted Sound Field Distribution

Exploring the distribution of focused ultrasound field attracts more and more investigators' attention.Making use of the heat property of focused ultrasound, we can measure the distribution of temperature to calculate the distribution of focused ultrasound field. During the exploration, we found that the temperature rise rate had a liner relation to sound intensity. So we conducted experiments and got the infrared images with noise. In order to obtain an accurate distribution of focused ultrasound field, it's necessary to find out a solution to get rid of the noise in infrared images. In traditional, we use hydrophone to explore the distribution of focused ultrasound field even in nonlinear area. So the result got by hydrophone was considered as standard. So the investigation was focused on the experimental validation of a filter which was the most suitable way for image process of infrared chart. So the ability of the filter should be that removing most noise and the distribution of temperature rise rate is unchanged. Six kinds of filters were used to deal with the raw data to obtain related information, from the results, we drew a conclusion that gauss filter was superior to the others filter, and a non- distortion distribution of focused ultrasound field would be get by the use of Gaussian filter.     

ICA based speckle filtering for target extraction in SAR images using adaptive space separation

A novel approach based on independent component analysis (ICA) for speckle filtering and target extraction of synthetic aperture radar (SAR) images is proposed using adaptive space separation with weighted information entropy (WIE) incorporated. First the basis and the independent components are respectively obtained by ICA technique, and WIE of the image is computed; then based on the threshold computed from function T-WIE (threshold versus weighted-information-entropy), independent components are adaptively separated and the bases are classified accordingly. Thus, the image space is separated into two subspaces: "clean" and "noise". Then, a proposed nonlinear operator ABO is applied on each component of the 'clean' subspace for further optimization. Finally, recovery image is obtained reconstructing this subspace and target is easily extracted with binarisation. Note that here T-WIE is an interpolated function based on several representative target SAR images using proposed space separation algorithm.     

基于复轮廓波域高斯比例混合模型SAR图像去噪

在分析了SAR图像的噪声成因及其噪声模型的基础上,提出了一种适用于复轮廓波变换域的高斯比例混合模型的SAR图像去噪（CCT-GMS）算法.本文所提出的算法具有多方向多尺度移不变性,并且充分的利用了复轮廓波的时域和频域的特性,改善了图像的视觉效果.实验结果表明：相比使用小波-轮廓波加上Cycle Spinning去噪,本文算法的峰值信噪比提高2 dB,相比使用BLS-GMS去噪,本文的算法抑制了人造纹理产生,视觉效果得到了明显的改善.     

微区位移场的SEM散斑测量方法研究

本文研究了细观力学的一种新的实验方法，利用扫描电子显微镜拍摄金属材料表面的微区散斑图象，再对变形前后微区表面移场进行数字散斑相关计算，从而实现微区表面位移场的定量测量。文中验证了测量方法的可行性，并实测拉伸件表面微区位移场。     

超声波检测在钢管砼桥梁施工质量控制中的作用

在钢管砼桥梁中,钢管内砼的压注质量是保证桥梁总体质量的关键.通过超声波检测的原理和方法的介绍,以合阳嘉陵江大桥利用超声波检测确定出主弦管内砼的质量问题,有针对性地进行整改的工程实例,阐述了超声波检测在钢管砼桥梁质量控制中的重要地位和作用.     

超声波检测在钢管砼桥梁施工质量控制中的作用

在钢管砼桥梁中,钢管内砼的压注质量是保证桥梁总体质量的关键.通过超声波检测的原理和方法的介绍,以合阳嘉陵江大桥利用超声波检测确定出主弦管内砼的质量问题,有针对性地进行整改的工程实例,阐述了超声波检测在钢管砼桥梁质量控制中的重要地位和作用.     

Multi-band Image Registration Method Based on Fourier Transform

This paper presented a registration method based on Fourier transform for multi-band images which is involved in translation and small rotation. Although different band images differ a lot in the intensity and features,they contain certain common information which we can exploit. A model was given that the multi-band images have linear correlations under the least-square sense. It is proved that the coefficients have no effect on the registration progress if two images have linear correlations. Finally, the steps of the registration method were proposed. The experiments show that the model is reasonable and the results are satisfying.     

New Method of Reconstruction from Nonparallel Stereo and Application to Surgical Navigator

A new method to reconstruct 3D scene points from nonparallel stereo is proposed. From a pair of conjugate images in an arbitrarily configured stereo system that has been calibrated, coordinates of 3D scene points can be computed directly using the method, bypassing the process of rectifying images or iterative solution involved in existing methods. Experiment results from both simulated data and real images validate the method. Practical application to surgical navigator shows that the method has advantages to improve efficiency and accuracy of 3D reconstruction from nonparallel stereo system in comparison with the conventional method that employs algorithm for standard parallel axes stereo geometry.     

基于结构性字典学习的高光谱遥感图像分类

为提高高光谱遥感图像的分类精度,提出了一种新的结构性稀疏表示及字典学习的高光谱遥感图像分类方法.该方法能同时利用高光谱遥感图像像素间的空间及光谱关系得到表示每个像素的字典,被划分为同一像素组的像素具有通用的稀疏模式;由字典计算图像的稀疏表示系数获得遥感图像的稀疏表示特征;利用线性支持向量机算法实现对高光谱遥感图像的分类.对AVIRIS和ROSIS高光谱遥感图像进行的实验结果表明:提出的方法比普通字典学习分类精度分别提高0.041 1和0.046 6,Kappa系数分别提高0.179 3和0.056 3.      

基于球面图像的三角网格模型分割

为了从局部形状的角度实现对三角网格模型的管理和重用,提出了一种基于球面图像的三角网格模型分割方法.通过球面参数化及球面划分,将三角网格模型的表面属性信息映射到球面图像中;利用成熟的区域生长、区域合并图像分割算法对球面图像进行分割;将球面图像的分割结果转换为三角网格模型的分割结果.实验结果表明:该分割方法可以对不均匀的低分辨率三角网格模型进行有效分割,降低了几何属性估算对分割结果的影响,不会发生过分割现象,不需要进行分割的后续处理.     

数学形态学在工程图表计算机处理中的应用

对计算机辅助机械设计中经常遇到的图表数据类型的处理方式进行了讨论。和以往不 同的是, 将图表作为图象对待, 应用数学形态学对图表图象进行处理, 产生便于查询 的矢量化的图表曲线, 不但提高了参数选择的准确性, 而且也提高了利用计算机进 行机械设计的自动化程度。      

光源对位置敏感传感器定位精度的影响

介绍了位置敏感传感器的定位原理,研究了光源对其探测精度的影响。利用有限元分析软件FlexPDE对PSD数学模型进行模拟仿真,结果表明:光斑的半径与光斑所落的位置是影响定位精度的主要因素。     

海量影像数据的快速浏览设计

信息技术和传感器技术的飞速发展,使得遥感图像的数据量呈几何级数的递增.当浏览图像或缩放时传统的方法速度都比较慢,特别是缩小图像时要读取整个影像数据,而且还要间隔的抽取数据,速度之慢几乎难以忍受,当对影像数据进行数据矢量化的时候,工作效率就非常低.本文提出了一种在打开文件时花出一定时间对影像文件进行临时文件重建,做成倒金字分层结构,并通过内存映射文件读取数据,简化了文件读取操作.这样每次浏览或缩放图像时就可以无等待了.