Study on clear stereo image pair acquisition method for small objects with big vertical size in SLM vision system

Microscopic vision system with stereo light microscope (SLM) has been applied to surface profile measurement. If the vertical size of a small object exceeds the range of depth, its images will contain clear and fuzzy image regions. Hence, in order to obtain clear stereo images, we propose a microscopic sequence image fusion method which is suitable for SLM vision system. First, a solution to capture and align image sequence is designed, which outputs an aligning stereo images. Second, we decompose stereo image sequence by wavelet analysis theory, and obtain a series of high and low frequency coefficients with different resolutions. Then fused stereo images are output based on the high and low frequency coefficient fusion rules proposed in this article. The results show that Δw₁(Δw₂) and ΔZ of stereo images in a sequence have linear relationship. Hence, a procedure for image alignment is necessary before image fusion. In contrast with other image fusion methods, our method can output clear fused stereo images with better performance, which is suitable for SLM vision system, and very helpful for avoiding image fuzzy caused by big vertical size of small objects. Microsc. Res. Tech. 79:408–421, 2016. © 2016 Wiley Periodicals, Inc.     

Accurate shape from focus based on focus adjustment in optical microscopy

Optical microscopy allows a magnified view of the sample while decreasing the depth of focus. Although the acquired images from limited depth of field have both blurred and focused regions, they can provide depth information. The technique to estimate the depth and 3D shape of an object from the images of the same sample obtained at different focus settings is called shape from focus (SFF). In SFF, the measure of focus–sharpness–is the crucial part for final 3D shape estimation. The conventional methods compute sharpness by applying focus measure operator on each 2D image frame of the image sequence. However, such methods do not reflect the accurate focus levels in an image because the focus levels for curved objects require information from neighboring pixels in the adjacent frames too. To address this issue, we propose a new method based on focus adjustment which takes the values of the neighboring pixels from the adjacent image frames that have approximately the same initial depth as of the center pixel and then it re-adjusts the center value accordingly. Experiments were conducted on synthetic and microscopic objects, and the results show that the proposed technique generates better shape and takes less computation time in comparison with previous SFF methods based on focused image surface (FIS) and dynamic programming. Microsc. Res. Tech., 2009. © 2008 Wiley-Liss, Inc.     

基于小波变换和形态学的图像边缘检测方法

提出了一种基于小波变换和形态学的图像边缘检测方法。对源图像进行小波分解,用数学形态学法对低频子图像进行边缘检测,用小波变换法提取高频图像的边缘,采用一定的融合规则将两个边缘图像融合在一起得到一幅完好的边缘图像。这种边缘检测方法结合了小波变换法和数学形态学法的优点,对用这两种方法得到的边缘信息进行融合,有效地抑制了噪声,且边缘连续、清晰。实验结果表明,提出的这种结合方法优于单独使用数学形态学法或小波变换法。     

利用脉冲耦合神经网络的图像融合

为了获得对同一场景更为准确、全面和可靠的图像描述,提出了一种基于脉冲耦合神经网络(PCNN)的图像融合方法。将多源传感器图像配准后的各个源图像用9/7小波变换的提升算法进行分解,从而得到各个源图像的低频分量和高频分量。对于低频分量,采用像素绝对值选大法进行融合;而高频分量则作为PCNN的输入,在迭代结束后,通过比较PCNN点火次数得到一系列融合子图像;然后,用9/7小波的提升算法将获取的一系列多尺度融合子图像进行反变换得到最终的融合图像。设计了可见光图像与红外图像的融合实验,对融合图像的熵、平均梯度、标准差、空间频率进行了定量比较。当使用标准源图像进行融合时,各值比使用传统小波变换与PCNN相结合的图像融合方法分别高0.0104,0.2459,0.1131和0.2846。     

SLM彩色显微图像的亚像素边缘检测方法

微操作技术的迅速崛起迫切要求显微图像处理技术的发展。在HSI彩色模型的基础上,根据SLM视觉系统的彩色显微图像特点,基于小波变换提出了一种适用于SLM彩色显微图像的边缘检测方法。根据三次样条拟合曲线的一阶导数零点,获取精确的亚像素边缘。试验证明,该方法适用于各放大倍率下的SLM彩色显微图像,能较好地滤除噪声,检测出完整的亚像素边缘。给出了利用该算法处理噪声仿真图像和真实SLM彩色显微图像的试验结果。     

基于图像融合的年轮细胞边缘检测算法研究

提出一种基于图像融合的边缘检测算法。首先对源图像进行小波分解,在不同分解层用小波模极大值法对高频子图像进行边缘检测,用数学形态学对低频子图像进行边缘检测,然后采用一定的融合规则将这两个边缘检测图像融合在一起。实践结果表明,这种方法优于单独使用小波模极大值法或数学形态学法,对噪声具有很好的鲁棒性,得到的图像边缘连续、清晰。     

基于非下采样双树复轮廓波变换和稀疏表示的红外和可见光图像融合

提出了一种基于非下采样双树复轮廓波变换(NSDTCT)和稀疏表示的红外和可见光图像融合方法,以改善传统的基于小波变换的图像融合方法的不足。该方法首先利用形态学变换处理源图像,利用NSDTCT变换进行图像分解得到低频子带系数和高频子带系数。根据高低频系数的不同特点,提出改进的稀疏表示(ISR)的融合规则用于低频子带;然后将改进的空间频率作为脉冲耦合神经网络的外部输入,提出基于自适应双通道脉冲耦合神经网络(2APCNN)的融合策略用于高频子带。最后通过NSDTCT逆变换获得融合后的图像。实验结果表明:本文方法在客观指标和视觉效果方面均优于传统图像融合的方法。与传统的NSCT-SR方法相比,实验的两组图像中4个客观指标:互信息(MI)、边缘信息保留量QAB/F,平均梯度(AG)和标准差(SD)分别提高了9.89%、6.39%、104.64%、55.09%和9.53%、17.77%、95.66%、52.89%。     

基于光纹特征的激光主动照明图像去模糊

受光学系统离焦、大气扰动、平台振动的影响,激光主动照明系统捕获的图像容易被模糊,而传统的去模糊方法难以取得良好的复原效果,故本文提出基于光纹特征的盲解卷积复原方法来实现图像去模糊。首先将模糊图像降采样,建立尺度金字塔,在尺度空间查找光纹特征图像块。随后基于激光主动照明图像饱和像素较多的特点,提出新的图像退化模型。最后针对模糊核估计、光纹参数更新、清晰图像复原3个步骤,提出适用的能量函数,迭代复原出无噪清晰图像。搭建了主动照明系统,在捕获的激光主动照明图像上进行了实验,并与现有方法进行了对比。结果表明:本文方法不仅能够复原出清晰图像,而且能有效抑制振铃效应,其客观评价指标峰值信噪比(PSNR)优于已有的其他算法。     

Image distortion correction for micromanipulation system based on SLM microscopic vision

Stereo light microscope (SLM) simulates stereo imaging principle of human eyes. Microscopic vision system based on SLM has become an important visual tool for micro measurement, micromanipulation, and microinjection. We develop a micromanipulation system based on SLM and present an image distortion correction method. We mainly correct two kinds of image distortions: lateral and vertical distortion. Distortion correction consists of two steps. First, a linear fitting algorithm for each row or column of target points is developed, and the fitting errors are calculated. If the fitting errors are smaller than a given threshold, the linear fitting results are kept and used. Otherwise polynomial fitting procedure will be used. Second, the parallelism of straight lines is corrected. The results show that a line in world coordinate frame (WCF) is not necessarily a straight line in image coordinate frame (ICF), or two parallel lines in WCF may be not parallel in ICF. Distortion correction can restore the parallel and linear relationship. For distorted left and right images, the magnitude of distortion exceeds 6 pixels and 4 pixels in the horizontal direction, and 1.2 pixels and 1.7 pixels in the vertical direction, respectively. After corrected, for left and right image, distortion can be reduced to 0.8 pixels and 0.7 pixels in the horizontal direction, and 0.96 pixels and 1.3 pixels in the vertical direction, respectively. The results show that distortion parameters obtained from the proposed method can effectively correct distorted images. Microsc. Res. Tech. 79:162–177, 2016. © 2016 Wiley Periodicals, Inc.     

采用非采样Contourlet变换与区域分类的红外和可见光图像融合

提出基于多尺度变换和区域相结合的红外与可见光图像融合方法,用于有效保留红外图像与可见光图像中的空间信息及热目标信息,提升融合图像的可观测性和可理解性。首先,基于非采样Contourlet变换(NSCT)方法对红外和可见光图像进行初步融合,采用基于局部能量的规则融合低通子带系数,根据尺度内各方向子带的相关性原则融合带通方向子带系数。然后,计算初次融合后所得的融合图像与源图像的结构相似性(SSIM),根据源图像与初次融合图像的结构相似程度对图像进行区域分类,得到相似区域分类标识图。最后,依据区域内各自的相似度特性,分别采用不同的融合策略进行二次融合,从而得到最终的融合结果。实验结果表明:该方法能够充分提取源图像的区域特征和纹理特征,融合结果在主观和客观评价上均优于目前流行的融合方法。与仅使用NSCT法进行融合相比,实验所采用的两组图像的质量评价指标分别提高了16%、85%、54%、36%和18%、102%、84%、41%。表明该方法在主客观评价上均优于双树复杂小波变换(DTCWT)、NSCT、冗余离散小波变换(RDWT)等方法。     

基于WEMD和生成对抗网络重建的红外与可见光图像融合

针对红外与可见光图像融合中边缘模糊、对比度较低的问题,提出一种二维窗口经验模式分解(WEMD)和生成对抗网络重建的红外与可见光图像融合算法.将红外和可见光图像进行WEMD分解得到内蕴模式函数分量和残余分量,将内蕴模式函数分量通过主成分分析进行融合,残余分量用加权平均进行融合,重构得到初步融合图像,再将初步融合图像输入生...     

模拟生物视觉机制的彩色人脸识别方法

为了充分利用彩色图像提供的信息提高人脸识别的性能,提出了一种模拟生物视觉机制的彩色人脸识别方法。该方法首先构造一种模拟人类的色彩感知机制的对立色模型,将彩色人脸图像描述为对立色形式。然后,模拟初级视皮层的信息处理机制,从图像对立色描述的亮度分量和色度分量分别提取人脸的纹理特征和色彩特征。最后,分别对纹理特征和色彩特征进行分类识别,并将二者的识别相似度融合得到最终的人脸识别结果。该方法利用对立色模型提高了色彩特征对光照变化的鲁棒性,并且综合利用彩色图像的色彩和纹理信息提高了人脸识别的精度,特别是对模糊图像的识别精度。在彩色FERET人脸库和AR人脸库上的实验表明,相对于直接对灰度图像进行识别的方法,该方法对清晰图像的识别率提高了4.5%～16.3%,而对模糊图像的识别率提升更加显著。     

交叉双边滤波和视觉权重信息的图像融合

图像融合技术是图像分析领域重点研究内容之一,为了更好地保留原图像中的细节信息,提高融合图像的对比度,提出了基于视觉权重图的多尺度图像融合方法。首先,利用可变参数的交叉双边滤波器对两幅待融合图像进行多尺度分解;然后,在每个分解层分别计算相应的视觉权重图,并针对不同分解层赋予不同的权重值;最后,综合这些结果生成融合图像。由于对原始图像的分解没有采用下采样和上采样操作,因此不会损失图像中的信息,且克服了传统像素级融合方法中融合图像模糊、对噪声敏感等不足。通过4种定量分析实验表明,在多种模式的图像融合应用中,本方法优于其他5种对比方法,融合时间小于0.2 s。融合后图像细节信息、对比度得到增强,同时降低处理时间。     

基于小波系数邻域特征的图像融合

在利用小波变换进行图像融合的基础上,研究了融合因子的选取方法。由于小波变换在时域和频域中同时具有良好的局部特性,为了很好地利用小波变换的这种特征,提出了利用小波系数的邻域特征(邻域方差)来定义融合因子的思想。评价融合算法的性能应该从融合图像的信息增加量和融合图像的失真度两个方面来评价,融合图像的熵用来描述融合图像的信息含量,相对熵可以描述融合图像的失真度,评价结果显示出其方法的实用性。实验表明该算法用于医学图像的融合能得到很好的效果。     

Fusion of GFP and phase contrast images with complex shearlet transform and Haar wavelet‐based energy rule

Image fusion techniques can integrate the information from different imaging modalities to get a composite image which is more suitable for human visual perception and further image processing tasks. Fusing green fluorescent protein (GFP) and phase contrast images is very important for subcellular localization, functional analysis of protein and genome expression. The fusion method of GFP and phase contrast images based on complex shearlet transform (CST) is proposed in this paper. Firstly the GFP image is converted to IHS model and its intensity component is obtained. Secondly the CST is performed on the intensity component and the phase contrast image to acquire the low‐frequency subbands and the high‐frequency subbands. Then the high‐frequency subbands are merged by the absolute‐maximum rule while the low‐frequency subbands are merged by the proposed Haar wavelet‐based energy (HWE) rule. Finally the fused image is obtained by performing the inverse CST on the merged subbands and conducting IHS‐to‐RGB conversion. The proposed fusion method is tested on a number of GFP and phase contrast images and compared with several popular image fusion methods. The experimental results demonstrate that the proposed fusion method can provide better fusion results in terms of subjective quality and objective evaluation.     

Multifocus watermarking approach based on discrete cosine transform

Image fusion process consolidates data and information from various images of same sight into a solitary image. Each of the source images might speak to a fractional perspective of the scene, and contains both “pertinent” and “immaterial” information. In this study, a new image fusion method is proposed utilizing the Discrete Cosine Transform (DCT) to join the source image into a solitary minimized image containing more exact depiction of the sight than any of the individual source images. In addition, the fused image comes out with most ideal quality image without bending appearance or loss of data. DCT algorithm is considered efficient in image fusion. The proposed scheme is performed in five steps: (1) RGB colour image (input image) is split into three channels R, G, and B for source images. (2) DCT algorithm is applied to each channel (R, G, and B). (3) The variance values are computed for the corresponding 8 × 8 blocks of each channel. (4) Each block of R of source images is compared with each other based on the variance value and then the block with maximum variance value is selected to be the block in the new image. This process is repeated for all channels of source images. (5) Inverse discrete cosine transform is applied on each fused channel to convert coefficient values to pixel values, and then combined all the channels to generate the fused image. The proposed technique can potentially solve the problem of unwanted side effects such as blurring or blocking artifacts by reducing the quality of the subsequent image in image fusion process. The proposed approach is evaluated using three measurement units: the average of Q^abf, standard deviation, and peak Signal Noise Rate. The experimental results of this proposed technique have shown good results as compared with older techniques. Microsc. Res. Tech. 79:431–437, 2016. © 2016 Wiley Periodicals, Inc.     

结合引导滤波和卷积稀疏表示的红外与可见光图像融合

为了解决红外与可见光图像融合时信息容易相互干扰、影响融合质量的问题,将引导滤波、高斯低通滤波与非下采样方向滤波器组相结合,提出一种新的图像融合方法。利用引导滤波和高斯低通滤波,将源图像分解为低频近似部分、强边缘部分和高频细节部分,并将高频细节部分进行非下采样方向滤波,进一步得到高频方向细节部分;对低频近似部分应用基于局部区域能量的融合规则,对强边缘部分提出一种基于卷积稀疏表示的融合规则,对高频方向细节部分提出改进的脉冲耦合神经网络的融合规则,得到相应的融合部分,并通过逆变换得到最终的融合图像。对多组红外与可见光图像的实验结果表明,算法得到的融合结果的主观视觉效果和客观评价指标均优于传统的图像融合方法,其客观评价指标中的标准差、信息熵、互信息、平均梯度和空间频率相比融合效果较好的基于离散小波变换和稀疏表示的融合方法平均提高20.28%、2.24%、47.41%、5.34%、8.02%。     

基于多小波的图像处理在电晕检测中的应用

提出了基于多小波变换的图像处理方法,该方法以多小波变换为基础,在一次多小波分解与重构之间完成双谱段图像处理.首先进行多小波变换,将变换系数进行软阈值收缩消去噪声;然后根据图像中需增强的信息,选择增强系数进行子带增强;最后提出一种新的自适应权值融合规则,采用这个规则融合变换系数,进行小波重构得到处理后的单幅图像.实验表明,这种方法不仅能提高图像的视觉效果,增强源图像的边缘信息,而且能很好地将源图像中列电晕检测有用的信息融合在一起,提高电晕检测系统的定位精度.     

改进的响尾蛇双模式细胞模型的图像融合

由于基于经典Waxman融合模型得到的伪彩色融合图像目标不够清晰,本文提出了一种改进的感受野融合模型。对红外图像和可见光图像分别进行了ON对抗增强和OFF对抗增强;将红外ON对抗增强图像馈入中心-环绕感受野模型的中心兴奋区域,可见光OFF对抗增强图像馈入环绕抑制区,得到融合图像的B分量;将红外OFF对抗增强图像馈入中心-环绕感受野模型的环绕抑制区域,可见光ON对抗增强图像馈入中心兴奋区,得到融合图像的G分量;将可见光ON对抗增强图像直接作为融合图像的R分量;然后,输出RGB伪彩色融合图像。最后,用Waxman方法和本文提出的方法分别对两组源图像进行融合,并用信息熵和平均梯度对融合结果进行了评价。结果表明,采用提出的模型,第一组融合图像的信息熵和平均梯度比Waxman融合模型分别高出0.314 6和0.004 1,第二组融合图像的信息熵和平均梯度比Waxman融合模型分别高出0.255 1和0.002 7。得到的数据显示本文提出的融合模型的融合效果优于经典Waxman模型。     

光电混合联合变换相关器中各元器件结构参数之间的关系

分析了空间光调制器(SLM)和面阵CCD的像元结构对输入图像和功率谱的抽样,以及抽样对光电混合联合变换相关器(JTC)性能的影响;推导出了光电混合JTC中,SLM、面阵CCD、傅里叶变换透镜、输入图像等各结构参数之间应满足的关系。根据推导出的关系公式,结合实验所用透镜、SLM、CCD的各项参数,选择不同的图像间距,对联合变换相关识别过程进行了模拟验证。输入大小都为32×32像素的参考图像和目标图像,当两者间距大于64像素且小于374像素时,可以得到理想的识别效果;间距小于64像素时,同级输出光场的自相关和互相关信号不能完全分离;间距大于374象素时,相邻两级互相关信号交叠错位;当间距大到超过405像素时,无法进行相关识别。模拟结果与理论推导一致。这些关系对JTC的设计及应用有重要意义。