强噪声背景下基于非网格MRF的SAR图像快速分割方法

像素级的马尔可夫随机场图像分割算法,在强噪声的SAR图像中难以保证消除斑点噪声的同时不破坏图像的边缘结构.针对此,本文提出了一种新的分割方法,首先将图像划分为若干个内部连通且有良好边缘的小区域块,然后将区域块内像素灰度的均值作为块内每个像素的灰度强度以提高算法的抗噪能力.在迭代优化阶段,用区域块替代像素作为新的处理单元,从而减少处理单元的数目提高算法的运行效率.为验证新算法的性能,将其分别应用于人工合成图像和真实的SAR图像上,并与经典分割算法做比较显示出了本文算法在噪声抑制、边缘保护和运算效率方面的性能.     

基于Mean shift算法的灰度人脸跟踪

由于灰度图像的信息单一、缺乏描述目标的信息,且易受到光照的影响,导致Mean shift算法在灰度图像跟踪中的应用不稳定,我们采用结合灰度与方向编码特征建立目标模型的策略,提出了在灰度图像中以Mean shift为核心的人脸跟踪算法.实验结果表明,该算法可以成功的克服混乱、遮挡、光照变化以及目标自身的缩放与旋转的影响,并且计算量非常小,对于大小为48像素×68像素的目标,整个算法的计算时间仅为34ms.     

基于量子核聚类算法的图像边缘特征提取研究

为了提高图像边缘特征提取质量,采取了量子核聚类算法。首先把像素映射量子编码,在码元建立域内对像素块进行随机采样;然后通过聚类距离计算数据点和每一个聚类核心的距离,把数据向量分配到距离最小的核心向量中,核函数确定有效影响范围;最后对像素聚类相异性分析,给出了算法流程。实验仿真显示这种算法对图像边缘特征提取轮廓清晰,连贯性好,评价指标MS和聚类准确率较好,算法收敛快。     

基于量子比特平面编码算法的图像重建研究

为了提高图像重建质量,提出量子比特平面编码算法。首先进行图像像素灰度段编码,获得中间段灰度级滤波矩阵;然后量子比特经过Walsh-Hadamard变换,将输入图像像素分解出低频部分和高频部分;接着分别对正系数矩阵和负系数矩阵扫描,在正负系数比特平面码流之间插入一个比特标志;最后给出了图像重建过程。实验仿真显示本文算法的重建效果清晰,指标分析图像信噪比最大,均方根误差较接近于0。     

基于无序分割投影策略与重力模型的图像加密算法

目的解决当前图像算法因其像素置乱和扩散操作与明文无关,导致其抗明文攻击能力较弱,且其置乱过程存在周期性,使其安全性不佳等问题。方法提出基于无序分割投影策略与重力模型的图像加密算法。首先对输入明文进行无序分割,获取重叠子块,并构建每个子块的位置坐标计算模型,输出图像子块的位置;根据明文像素量计算Kent映射的初值,通过迭代Kent映射获取随机序列组;定义位置置乱机制,对重叠子块进行混淆;再引入分割投影策略,互换每个置乱子块中的像素位置,再对其重组,输出置乱密文;通过设计像素质量变化函数替换重力模型的固定质量,改进重力模型,对置乱密文完成像素加密。结果实验结果显示与当前图像加密技术相比,文中算法具有更高的安全性,输出密文中的相邻两像素间的关联度最低,具有更强的抗明文攻击与剪切攻击性能。结论所提加密算法能够较好地用于图像信息安全传输,具有较好的应用价值。     

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.     

增强彩色电子纸饱和度的误差扩散优化

为解决彩色电泳电子纸因粘滞阻力等引起的显示颜色饱和度低、边缘模糊等问题,本文提出基于HSL空间的彩色电子纸边缘增强误差扩散算法,以提高图像显示质量。该算法首先将去噪图像利用边缘检测算子得到边缘增强图像,结合边缘增强图像像素邻域平均灰度、像素与邻域灰度差异和像素邻域相似度得到新RGB图像像素值。接着,新RGB图像通过阈值处理过程得到16色阶RGB图像。最后,16色阶RGB图像转换到HSL空间,建立HSL和RGB色彩空间的转换模型,根据像素点的亮度和饱和度计算出调整因子,从而增强RGB图像饱和度。该算法与传统的误差扩散算法相比,信噪比PSNR提高了3.9%～26.7%,UCIQE提高了10.1%～48.2%,相似度SSIM提高了13.2%～25.4%。主观评价参考ITU-R BT.500-1标准设计实验计算Z得分,最终本文算法处理后图像在彩色电子纸上显示的图像细节和颜色更加接近原图,整体视觉效果更好。     

基于方块编码的图像特征提取及检索算法

提出了一种基于方块编码的图像检索算法.首先将图像分成互不重叠的子图像块,根据图像块中各像素间的色差,利用方块编码的思想对这些子图像进行编码,然后根据人眼的视觉特性来定义图像的关键块,最后借助于基于关键字的文本检索技术进行图像检索.同时,考虑到不同类型的关键块在表征图像内容时重要程度的不同而赋予其不同的权值.实验结果表明本文算法在图像的相似性检索时是有效的,并具有较高的检索效率.     

四边形分片逼近控制点的图像畸变校正算法

针对传统的图像畸变校正算法建模复杂、实时性差且图像信息易丢失等缺点,提出了一种基于四边形分片逼近控制点的图像畸变校正算法.该方法以标准点阵图像作为量测目标,将数学形态学和滑动邻域操作相结合以确定畸变图像像素点质心,采用基于四边形分片逼近的方法来拟合高次多项式校正模型,运用两步一维线性灰度级插值向后映射算法确定输出图像中像素点的灰度.将该算法在TMS320DM6437 DSP上实现,实验结果表明,校正一幅像素为768×494的图像所用的时间为0.036 S,畸变校正的误差在0.31个像素以内,有效地避免了边缘信息丢失、空洞及灰度失真现象.     

基于频率分级的指纹图像压缩算法

指纹图像是由黑白相间的脊线、谷线排列在一起而构成的特殊灰度图像,反复出现的反差边缘、周围的背景区域使得指纹图像具备低、中、高三种不同的频率成分,本文利用小波包变换和频谱分析提出了一种基于频率分级的指纹图像压缩算法,对包含能量最多的低频子图像,采用无损差分脉冲编码(DPCM)算法;对包含能量较少的中频子图像,采用嵌入式小波零数编码(EZW)算法;对包含能量最少的高频子图像,采用集合分裂嵌入块编码(SPECK)算法。仿真实验表明,本算法在保证重建质量的前提下,压缩比平均提高了21.4%左右,逼真度平均提高了6.25%左右。     

二维码印刷质量参数的影响因素分析

二维码印刷质量直接影响条码信息传递的准确性。为了分析影响二维码印刷质量的主要因素,基于二维码检验国家标准,研制了二维码图像采集平台。通过制作二维码测试样本,分析了灰度变化和几何变化对符号反差、调制比、轴向不一致、网格不一致等二维码印刷质量参数的影响。实验结果得出不同二维码质量参数分级的图像质量要求,为二维码的印刷质量检测和控制提供参考依据。     

一种似然曲线的图像拼接的改进算法

本文在大量调研国内外的相关算法的基础上,介绍了图像拼接的算法分类,并提出了一种基于灰度似然曲线的寻找匹配点的改进算法.其算法原理为首先进行匹配点的粗匹配,再进行改进后的似然曲线快速拼接,其不但保持了原始算法的精度,而且大大的加快了速度.通过仿真实验,在精度不变的情况下,对应于不同图像,速度较原始方法提高了约60%.     

A Method of Identifying Thunderstorm Clouds in Satellite Cloud Image Based on Clustering

In this paper, the clustering analysis is applied to the satellite image segmentation, and a cloud-based thunderstorm cloud recognition method is proposed in combination with the strong cloud computing power. The method firstly adopts the fuzzy C-means clustering (FCM) to obtain the satellite cloud image segmentation. Secondly, in the cloud image, we dispose the ‘high-density connected’ pixels in the same cloud clusters and the ‘low-density connected’ pixels in different cloud clusters. Therefore, we apply the DBSCAN algorithm to the cloud image obtained in the first step to realize cloud cluster knowledge. Finally, using the method of spectral threshold recognition and texture feature recognition in the steps of cloud clusters, thunderstorm cloud clusters are quickly and accurately identified. The experimental results show that cluster analysis has high research and application value in the segmentation processing of meteorological satellite cloud images.     

Droplet Image Super Resolution Based on Sparse Representation and Kernel Regression

Microgravity and containerless conditions, which are produced via electrostatic levitation combined with a drop tube, are important when studying the intrinsic properties of new metastable materials. Generally, temperature and image sensors can be used to measure the changes of sample temperature, morphology and volume. Then, the specific heat, surface tension, viscosity changes and sample density can be obtained. Considering that the falling speed of the material sample droplet is approximately 31.3 m/s when it reaches the bottom of a 50-meter-high drop tube, a high-speed camera with a collection rate of up to 10⁶ frames/s is required to image the falling droplet. However, at the high-speed mode, very few pixels, approximately 48-120, will be obtained in each exposure time, which results in low image quality. Super-resolution image reconstruction is an algorithm that provides finer details than the sampling grid of a given imaging device by increasing the number of pixels per unit area in the image. In this work, we demonstrate the application of single image-resolution reconstruction in the microgravity and electrostatic levitation for the first time. Here, using the image super-resolution method based on sparse representation, a low-resolution droplet image can be reconstructed. Employed Yang’s related dictionary model, high- and low-resolution image patches were combined with dictionary training, and high- and low-resolution-related dictionaries were obtained. The online double-sparse dictionary training algorithm was used in the study of related dictionaries and overcome the shortcomings of the traditional training algorithm with small image patch. During the stage of image reconstruction, the algorithm of kernel regression is added, which effectively overcomes the shortcomings of the Yang image’s edge blurs.     

基于 SDAE 的受损 QR 码恢复算法

目的针对包装产品外壳上黑白QR码易受到污渍侵蚀损坏,长期磨损易模糊,以及图像采集过程易出现失焦模糊、运动模糊,导致无法完成识别需求,提出一种基于栈式降噪自编码器的受损QR码恢复的预处理方法,达到显著修复包装产品上受损的QR码图像并提高其识别率的目的。方法通过深度学习模型栈式降噪自编码器,可以将受到噪声干扰的像素点根据受损像素数据映射到以标准数据为参照的高概率数值点,实现整个受损QR码基于像素点的重构恢复,从而提高识别率。结果通过对实验QR码进行高斯模糊、随机污渍侵蚀等多种方式的损坏,能够将识别率较低或完全不能识别的测试图像集恢复出高质量的QR码图像,显著地提高了识别率,并且速度快、可重复性好。结论采用基于栈式降噪自编码器的受损QR码恢复的预处理方法,能够重建受损的QR码,并可以广泛应用于包装产品QR码识别前的预处理,以提高识别率。     

A secure authentication watermarking for halftone and binary images

An authentication watermark is a hidden data inserted into an image that can be used to detect any accidental or malicious alteration in the image. Many authentication‐watermarking techniques for continuous‐tone images are described in the literature, but only a quite small number of secure authentication watermarking techniques are available for binary/halftone images. This article proposes a simple solution for inserting a secure authentication watermark in binary/halftone images. It consists of choosing a set of pseudo‐random pixels in the image, clearing them, computing the message authentication code (or the digital signature) of the now‐cleared image, and inserting the resulting code into the selected random pixels. Dispersed‐dot halftone images watermarked by the proposed technique present better visual quality than do watermarked generic binary images. However, in practice, the visual degradation is hardly noticeable in either case. The proposed technique seems to be the only binary/halftone watermarking scheme that can detect even a single pixel alteration in the host image. It can be used with secret‐key or public‐key ciphers. © 2004 Wiley Periodicals, Inc. Int J Imaging Syst Technol 14, 147–152, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20018     

Feature extraction through generalization of histogram refinement technique for local region‐based object attributes

Content based image retrieval (CBIR) is used to retrieve digital images from large databases. However, the problem of retrieving images on the basis of the contents remains largely unsolved. The proposed method of image retrieval is based on the information provided by histogram analysis of the intensity or grayscale values of images. Some additional properties are also calculated and used that are based on regional characteristics of various objects in the image. The need to retrieve the additional regional properties arises due to the fact that the standard histograms are insensitive to small changes in images. Many images of different types can have similar histograms, because, histograms provide only a coarse characterization of an image. This is the main disadvantage of using histograms. This research is based on the concept of Histogram Refinement (Pass and Zabih, IEEE Workshop Appl Comput Vision ( 1996 ), 96–102). Distributing the grayscale image intensities by splitting the pixels using their intensity values into several classes just like the histogram refinement method can provide an estimate of the object characteristics present in an image. After the calculation of clusters using a color refinement method, the inherent features of each of the clusters is calculated based on the regional properties of the clusters. These additional region based features expound some structural information of the image. Finally, all of these features are used for image retrieval. © 2011 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 21, 298–306, 2011;     

一种感兴趣区域防溢出数字水印算法

目的针对工程设计图纸、医学影像等存在大量边缘值像素点的图像在嵌入水印时容易出现像素值溢出的问题,文中提出一种基于感兴趣区域防溢出的水印方案。方法该方案使用改进后的区域生长法分割原始图像得到不规则形状的ROI,再通过填充像素值得到矩形水印嵌入区域,对该区域进行提升小波变换,并经过Arnold置乱,通过对水印嵌入区域的分块和扫描,跳过边缘像素值,使用奇偶映射的方法将制成QR码的水印信息嵌入至宿主图像。结果嵌入水印后图像边缘仍完整,像素值溢出现象得到大大改善,嵌入水印后图像峰值信噪比高于48db,水印不可见性高于一般水印嵌入方案,满足高精度图像对水印不可见度要求,且经过攻击后仍能实现水印的提取。结论该方案充分考虑到含有大面积背景和大量边缘像素值图像的特点,保证认证水印嵌入至图像关键ROI区域,在保证原图质量的基础上实现了防溢出的水印嵌入,经过攻击后提取的水印仍能够读取认证信息,在包装印刷工程中具有实际应用价值。     

实际边缘轮廓下的螺栓综合尺寸质量检测

为了检测螺栓的尺寸质量,提出一种基于实际边缘轮廓的螺栓综合尺寸质量检测算法.该算法首先根据螺栓图纸公差要求,设计螺栓综合尺寸公差带图作为模板图;然后对螺栓图像进行预处理,包括三段线性灰度增强、中值滤波和最大类间方差法等;进一步将螺栓图像旋转为水平位姿并进行canny边缘检测,将螺栓图像和模板图裁剪,得到具有相同位姿、尺...