Karhunen-Loeve及多尺度金字塔联合变换的彩色逆半调算法

红绿蓝(RGB)颜色空间中的各颜色分量具有高度相关性,直接分通道实施的彩色逆半调方法会残留大量人眼敏感的半调纹理,且逆半调图像色偏较大。从分析矢量误差分散半调系统模型入手,推导其加噪特性,针对性地提出了一种Karhunen-Loeve(K-L)及多尺度金字塔联合变换的彩色逆半调算法。算法以K-L变换减弱彩色分量相关性,再利用多尺度中值金字塔算子以及维纳(Wiener)滤波分离并抑制高频细节子图中的半调噪声,最后进行中值金字塔、K-L逆变换重构结果图像。实验表明,该算法能有效去除半调噪声、减小重建图像的颜色偏差,与直接分通道逆半调算法相比峰值信噪比值提高约2~3 dB,且重建图像视觉效果良好。     

Hiding a checkered-pattern carrier-screen image in a camouflaged halftone image

As carrier-screen images, we have developed checkered-pattern carrier-screen images, which can be physically decoded by superimposing a checkered pattern. We also proposed a decoding method by image sampling with an ordinary compact digital camera. To obtain a better decoding result, each carrier-screen image should be output at a low resolution. However, secret information can be detected when you observe the image carefully. Thus, a hiding process is an important technique. In this paper, we propose an advanced hiding method by embedding the carrier-screen image into another significant image to generate a camouflaged halftone image. The proposed embedding method can be performed through a simple sequential process of blending and halftoning.     

Look-up table and Gaussian filter-based inverse halftoning method excellent in gray-scale reproducibility of details and flat regions

Halftoning is a technique in which gray-scale images are converted into binary ones, and has been used widely in many practical image processing applications. On the other hand, inverse halftoning is a technique of reproducing a grayscale image from a binary one. One of the sophisticated inverse halftoning methods which can yield a high quality grayscale image is that based on a look-up table (LUT). In this paper, a new inverse halftoning method based on a combination of this LUT method and a Gaussian filter is discussed. Here, the output gray-scale image is reproduced by blending the output of the LUT-based inverse halftoning and that of the Gaussian filtering appropriately in accordance with local statistics of the image. The effectiveness and the validity of the described method are verified through experiments.     

Suppression of moiré fringes due to sampling of halftone screened images

When a halftone screened image is discretely sampled by, for example, a CCD array, moiré fringes sometimes appear. These moiré fringes are caused by aliasing errors due to the improper sampling rate. To suppress these fringes, a dual sampling method is proposed. In this method, halftone screened images are sampled twice with different sampling rates, and the selection of proper frequency components less suffering from aliasing errors can effectively suppress moiré fringes.     

Bayes-optimal solution to inverse halftoning based on statistical mechanics of the Q-Ising model

On the basis of statistical mechanics of the Q-Ising model, we formulate the Bayesian inference to the problem of inverse halftoning, which is the inverse process of representing gray-scales in images by means of black and white dots. Using Monte Carlo simulations, we investigate statistical properties of the inverse process, especially, we reveal the condition of the Bayes-optimal solution for which the mean-square error takes its minimum. The numerical result is qualitatively confirmed by analysis of the infinite-range model. As demonstrations of our approach, we apply the method to retrieve a grayscale image, such as standard image Lena, from the halftoned version. We find that the Bayes-optimal solution gives a fine restored grayscale image which is very close to the original. In addition, based on statistical mechanics of the Q-Ising model, we are sucessful in constructing a practically useful method of inverse halftoning using the Bethe approximation.      

半色调编码计算全息图的数字水印方法

提出一种新的基于信息光学的数字水印方法。该方法将水印信息隐藏于半色调编码的计算全息图之中。通过相位复原技术将需隐藏的水印信息编码为相位函数嵌入在复波前中,其振幅定义为宿主图像,通过计算全息记录复波前并对全息图进行半色调编码完成水印信息的嵌入。水印的提取过程只需对含有水印信息的半色调图像进行光学或数字的傅里叶变换即可完成。并给出了算法有效性的理论分析和仿真实验结果。结果证明这种水印技术对于各种数字图像处理操作具有很高的稳健性,且半色调编码图的二值特性使嵌入水印具有很强的抗打印、抗复印、抗扫描的能力。     

Reconstruction of holograms generated by using a combination of an iterative method and an error diffusion method

Two-level quantized phase holograms produced by using a combination of an iterative method and an error diffusion method are presented. By using a previously proposed iterative method, images reconstructed from two-level quantized phase holograms are rapidly improved with small amounts of iterative operations but further improvement of the image quality is difficult even if the iterations are greatly increased. Therefore, in order to exceed the improvement limitation of the image quality, the combination of the iterative method and an error diffusion method was used for the hologram-making process. Experimental results using the combination method showed better images than those obtained by the iterative method alone, when referred to results from synthesized holograms.     

双面半色调图像的光谱反射率色彩精确预测模型

为了准确地预测双面半色调图像的光谱反射率,并考虑光在纸张内的散射和油墨在纸基上的扩展渗透,建立了一个统一的双面半色调图像光谱反射率精确色彩预测模型.在油墨是非散射介质,纸张为强散射体以及油墨和纸张具有相同的折射率的条件下,引入Williams-Clapper模型中光在油墨中斜程传播的思想,考虑进入纸基层的光线横向传播和油墨扩展导致的网点扩大效应以及光在纸基和印刷品-空气界面间的多重内反射,利用多重内反射的网状结构分析法和最小二乘曲线拟合方法,确定了各种不同叠印条件下的理论网点面积率和有效网点面积率的函数关系,得出彩色双面图像的光谱反射色彩精确预测模型.新模型的预测值和测量值达到了较好的匹配,同时这也为彩色双面图像的呈色规律分析和印刷品质量检测系统的研制与开发提供了理论依据.     

基于脑模型控制器的红外背景预测算法

在分析云背景红外图像空间分布上存在混沌现象的基础上,提出一种基于脑模型控制器的红外背景预测算法.该方法利用混沌具有短时可预测性的特点,对云背景图像进行预测,并根据云背景杂波和运动目标的混沌特性差异修正预测模型.仿真结果表明,该算法能有效地提高云背景的预测准确度,预测残差符合白噪音特性,对云背景杂波具有良好的抑制效果,能显著提高目标的信杂比,从而改善目标的检测性能.     

A Hybrid Preaching Optimization Algorithm Based on Kapur Entropy for Multilevel Thresholding Color Image Segmentation

Multilevel thresholding segmentation of color images plays an important role in many fields. The pivotal procedure of this technique is determining the specific threshold of the images. In this paper, a hybrid preaching optimization algorithm (HPOA) for color image segmentation is proposed. Firstly, the evolutionary state strategy is adopted to evaluate the evolutionary factors in each iteration. With the introduction of the evolutionary state, the proposed algorithm has more balanced exploration-exploitation compared with the original POA. Secondly, in order to prevent premature convergence, a randomly occurring time-delay is introduced into HPOA in a distributed manner. The expression of the time-delay is inspired by particle swarm optimization and reflects the history of previous personal optimum and global optimum. To better verify the effectiveness of the proposed method, eight well-known benchmark functions are employed to evaluate HPOA. In the interim, seven state-of-the-art algorithms are utilized to compare with HPOA in the terms of accuracy, convergence, and statistical analysis. On this basis, an excellent multilevel thresholding image segmentation method is proposed in this paper. Finally, to further illustrate the potential, experiments are respectively conducted on three different groups of Berkeley images. The quality of a segmented image is evaluated by an array of metrics including feature similarity index (FSIM), peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and Kapur entropy values. The experimental results reveal that the proposed method significantly outperforms other algorithms and has remarkable and promising performance for multilevel thresholding color image segmentation.     

双面半色调图像的Clapper-Yule色彩预测分程模型

通过印刷品光谱反射比预测半色调图像色彩是印刷质量控制与设备检测研制领域十分关注的课题。在假定油墨是非散射介质以及油墨的折射率与纸张的折射率近似相等的条件下,利用光在油墨与纸张中散射迁移路径长短不同的分程理论和多重内反射的网状结构分析方法,研究了光照射在双面印刷品上的光谱反射规律,建立了双面印刷品的光谱反射色彩预测模型。并在此基础上通过理论分析,论证了新建双面印刷品的Clapper-Yule色彩分程预测模型的合理性。新模型为双面印刷品的呈色规律分析与印刷品在线检测仪的研制提供了理论依据。     

Bilateral two-dimensional least mean square filter for infrared small target detection

The basic TDLMS (Two-Dimensional Least Mean Square) filter fails to detect infrared small targets consistently, especially under conditions of heavy noise and distinct cloud edges. This paper proposes a robust and efficient small-target detection method based on the basic TDLMS filter. The method first smooths the input image with a Gaussian filter of adaptive variance, and then employs TDLMS with a selected step size to filter the image with rightward and leftward iterations. Two prediction error images are obtained by subtracting the prediction images of the bilateral filtering from the original input image. Each prediction error image is separated into positive and negative prediction error images. That is, four images are generated in the bilateral filtering. The final image is obtained by fusing these four images. Experimental results show that the proposed method achieves significant improvement in background suppression and detection performance over the basic TDLMS filter and other improved TDLMS filters.     

Multistage morphological segmentation of bright-field and fluorescent microscopy images

This paper describes the multistage morphological segmentation method (MSMA) for microscopic cell images. The proposed method enables us to study the cell behaviour by using a sequence of two types of microscopic images: bright field images and/or fluorescent images. The proposed method is based on two types of information: the cell texture coming from the bright field images and intensity of light emission, done by fluorescent markers. The method is dedicated to the image sequences segmentation and it is based on mathematical morphology methods supported by other image processing techniques. The method allows for detecting cells in image independently from a degree of their flattening and from presenting structures which produce the texture. It makes use of some synergic information from the fluorescent light emission image as the support information. The MSMA method has been applied to images acquired during the experiments on neural stem cells as well as to artificial images. In order to validate the method, two types of errors have been considered: the error of cell area detection and the error of cell position using artificial images as the “gold standard”.     

Effect of dynamic range input image on performance of binary subtracted joint transform correlator

A demand for the dynamic range of input images in the binary subtracted joint transform correlator was studied by computer simulations using input scenes containing multiple halftone images of human faces. To realize good discriminability the correlator requires use of an image-conversion subsystem with a dynamic range larger than 50:1 and 16:1 in amplitude for input scenes having (1) a reference image and many target images and (2) a target image and many reference images, respectively.     

半色调双面图像的色彩预测Clapper-Yule模型

为了准确地预测印刷图像的光谱反射率,在假定油墨是非散射介质以及油墨的折射率与纸张的折射率近似相等的近似下,利用考虑光在纸基内多次内反射的Clapper-Yule理论和描述多重内反射的网状结构分析模型,建立了同色不同加网周期双面墨像的光谱反射色彩预测模型.同时给出了包含纸基的向下体反射和反面纸基-空气构成界面定向反射作用的单面墨像Clapper-Yule色彩预测修正新模型.     

Measurement of histograms of halftone images

We present theory and experiments for two optical methods for measuring histograms of halftone images. In both methods, the histogram is obtained by spatial filtering of the halftone object. In the first method, we used a phase filter with a comb-type point spread function. In the second method, the filter matched one kind of the differentiated halftone dots. Experiments show that the first method works fast and gives fairly accurate results (errors were about 10%), whereas the second method requires more experimental efforts, but the results are more accurate in this case (errors were about 0.9%).     

超声全聚焦成像中等声程线伪影剔除方法

针对超声全聚焦成像算法中等声程线扩散产生的原理性伪影问题,提出了一种基于超声回波声场有效等声程线和图像强度分布特征相结合的伪影剔除方法。首先分析了全聚焦成像算法中等声程线产生伪影的机理,根据数据均方根误差自适应辨识有效等声程线;通过Canny算子获取全聚焦图像待处理候选区域,再根据候选区域中有效等声程线相交次数和图像强度的分布特征辨识缺陷图像和伪影,利用图像中强度最低像素值扩展填充剔除伪影后的区域,进而达到剔除伪影的目的。通过在不同直径通孔类和槽类标准缺陷试块上声场模拟实验,结果表明伪影剔除效果显著。同时,该方法对噪声也有一定的抑制能力,在不加滤波的条件下信号信噪比高于15 dB时就可获得较好的去伪影效果。     

荧光基半色调彩色图像的Clapper-Yule光学反射率

在假定成像基的吸收光谱与其荧光发射光谱不重合的近似下,采用考虑图像基多重内反射效应的半色调图像反射率预测Clapper-Yule方法研究了荧光基半色调图像的光强反射规律,得出彩色半色调图像反射率新模型.同时考虑了构成半色调图像网点的物理扩大对反射率的影响.     

一种抗光扰动的矢量纠偏方法研究

在半球成像系统实时跟踪目标的过程中,从受到光扰动影响的圆环像中迅速准确地提取圆环的中心是一个关键,为了适应半球成像系统跟踪目标的实时性和抗扰性能要求,根据圆的几何对称性,提出了一种矢量纠偏的抗光扰动的圆环中心确定方法,实验结果表明,对于无扰动的圆环图像其误差小于1个像素;对于有扰动的图环像误差不超过5个像素。     

去除乘性噪音的主成分分析算法

雷达成像系统的进一步应用依赖于对图像中噪音的有效抑制.在目前现有消除噪音方法的基础上,基于图像的局部相似性,结合主成分分析法,提出一种新的有效去除乘性噪音的滤波算法.乘性噪音经对数变换后可转化为加性噪音处理.分析了对数域中噪音的类型.首先在图像的对数域,通过非局部方法选取局部相似块作为训练样本,利用主成分分析法提取出信号的主要特征.然后基于统计理论中最小均方误差估计法给出了一种适用于图像信息的阈值原则.最后分析了变换过程引起的偏差,由对数域的偏估计得到滤波图像.数值实验验证了新算法的有效性.对比于目前提出的变分方法,新算法处理后的图像有更高的信噪比和更好的视觉效果,且具有一定的实用性.