压缩基础上利用纹理进行图像检索的方法研究

一幅图像的各个相邻像素之间是相关的,在对一幅图像进行检索的时候,总是提取图像的整体特征,所以一幅图像包含的信息对于检索来说是有冗余的.如果可以把冗余的信息减少,那么就可以大大提高检索的速度.采用高斯金字塔对其进行有效压缩,在压缩版本下提取图像纹理特征进而进行图像检索,大大加快了检索的速度和效率.实验证明,这种方法是有效的.     

三维CT层间图像超分辨重建与修复

CT图像在疾病诊断、癌症精准放疗阶段发挥着重要的作用.然而,受X射线剂量的限制以及现有医疗设备等因素的影响,三维CT图像成像采样间距较大,层间分辨率远低于层内分辨率.为提高CT图像的层间分辨率,避免因相邻层CT图像之间存在较大差异对超分辨率重建造成干扰,提出一种在相邻CT图像序列切片间利用上下层的配准信息插值出一个新的中间切片,并对插值得到的中间切片进行修复的方法.首先,利用CLG-TV光流估计模型配准算法估计相邻2幅CT图像之间的像素运动,得到一个稠密的光流场,从而获得2个连续切片之间精确的像素对应关系,并依据新切片位置对速度矢量进行缩放;然后,利用计算出的速度场在连续2幅图像之间生成初始插值图像.由于相邻切片之间的像素难以一一对应,插值后的图像通常存在像素缺失现象.最后利用序列图像的帧间非局部自相似性,通过求解最优化问题以修复插值图像中像素丢失的区域.在DIR-Lab实验室和山东省医学影像学研究所提供的数据集上的实验结果表明,与其他经典方法相比,文中方法能够生成高质量的中间CT切片,在定量和定性上提高了层间分辨率.     

共振算法用于图像分割

计算机视觉和识别技术在智能控制中的作用越来越重要.通过对利用共振理论进行图像分割方法的研究,提出了一个图像分割的实用算法,这通常是控制一个智能系统的第一步.共振算法是一种无教师学习算法,在门限的限定下用来将相邻的相同或相似的特征向量(或像素)组成同一特征空间(或区域).此算法在一定程度上容忍图像分割中出现的纹理特征强度逐渐变化现象.实验结果验证了共振算法是强调相邻特征相量(或像素)的相似性,而不是试图通过一个针对全局的门限来分割图像.     

一种提高计算机重构三维图像质量的方法

在全真三维场景的三维图像技术的研究中,根据计算机重构三维图像时分辨率低的问题,在基于透镜阵列模型的计算机II重构图像基础上,为提高质量和图像分辨率,提出一种基于相似像素块平滑过渡的图像后处理方法,方法对从每个元素图像中提取出的相邻像素块进行相似性判断,对相似像素块内中心像素以外的像素按照一定方法修改其灰度值,进行平滑,使图像后处理过程既缓解了从不同元素图像中提取的像素块间的灰度不连续性,又能保持重要的边缘信息,改善了重构图像的视觉效果.     

多摄像机图像拼接自动色彩均衡算法

针对多摄像机视频图像,分析了图像拼接技术中存在的问题,讨论了目前图像处理中常用的图像色彩均衡算法,提出了一种基于图像像素均值统计的亮度和色彩均衡处理算法。首先提取相邻两摄像机同步帧图像的重叠区域并对重叠区图像进行通道分离（RGB）,把其中一幅作为参考图像,另一幅作为目标图像,分别统计两幅图像各颜色通道像素均值差,用差值强制修正整幅目标图像。然后对修正后的图像和参考图像（整幅图像）进行颜色空间转换（RGB到HSV）,再次统计两幅图像亮度通道（V通道）均值差,用差值强制修正整幅目标图像亮度。实验结果证明,该算法能有效校正相邻摄像机图像的亮度和色差,对后期的拼接融合处理起到了很好的改善效果。     

基于像素相关性的数字图像隐写分析*

根据自然图像相邻像素之间具有一定相关性的特点,提出一种基于图像像素相关性度量的隐写分析方法。首先利用Hilbert空间填充曲线对图像各位平面像素以及图像像素进行扫描,构造一维序列,然后分别采用计算自相关系数和像素前后差值比的方法对图像相邻像素间的相关性进行度量,提取特征输入到分类器中,实验表明,该方法达到了较好的检测效果。     

综合引导滤波和字典学习超像素聚类图像融合

针对多聚焦图像融合易出现块效应和边界伪影等问题,提出了一种综合迭代引导滤波和字典学习超像素聚类的融合算法.首先对源图像进行超像素分割,利用密度峰值实现超像素的聚类,以超像素聚类块为处理单元提取特性形成特征矩阵;建立低秩表示模型,引入拉普拉斯正则项增加同类相邻区域空间一致性约束;构造低秩表示字典,借助自带二次惩罚项的线性交替迭代求解模型系数;通过联合低秩表示系数矩阵和误差矩阵构建初步聚焦特征图,利用迭代引导滤波优化聚焦特征图扩大多焦差异化,最后基于优化聚焦特征图和源图像获得最终融合结果.经仿真对比可知,提出算法的融合结果无论在主观视觉还是客观指标上都优于其他同类算法.     

具有纹理感知能力的超像素分割方法

目的 超像素分割是计算机视觉领域常用的一项预处理技术,目标是将相邻像素聚集成为具有一定语义的子区域,能够大幅度降低后续处理的计算复杂度,但是对包含强梯度纹理的图像分割效果不佳,为此提出一种具有纹理感知能力的超像素分割方法。方法 提出一种能够区分强梯度噪声和纹理像素的颜色距离,其中利用带方向的1/4圆形窗口均值滤波后的颜色信息,提升包含强梯度噪声和纹理图像的超像素分割性能。利用区间梯度幅值与Sobel梯度幅值相乘得到混合梯度幅值,具有纹理抑制、结构保持以及边缘线条细的优点,能够提升超像素的贴合边缘性能,增强超像素形状规则程度。最后,利用混合梯度的幅值计算具有结构回避能力的综合聚类距离,进一步防止超像素跨越物体的边界,增强超像素的贴边性能。结果 在BSDS500（Berkeley segmentation dataset 500）图像数据集和强纹理马赛克图像等不同类型图像上的测试结果显示,与目前主流的超像素分割方法相比,本文算法在UE （undersegmentation error）、ASA （achievable segmentation accuracy）和CM （compactness measure）等性能指标上分别提高了1.5%、0.2%和4.3%。从视觉效果上看,能够在排除纹理干扰的情况下生成结构边缘贴合程度更好的形状规则超像素。结论 本文算法在包含强梯度纹理图像上的超像素分割性能优于对比方法,在目标识别、目标追踪和显著性检测等易受强梯度干扰的技术领域具有较大应用潜力。     

大尺度遥感图像中港口目标快速识别

提出一种在大幅面灰度遥感卫星图像中快速识别港口目标的方法.通过对图像多分辨率处理,采用阈值方法进行海洋和陆地的分割,并在基于块的统计特征表示方法的基础上,建立快速分割中、小型港口候选区域方法,再根据港口的固有特征(半封闭区域)实现快速的港口目标识别.通过18幅大尺度图像对算法进行测试,测试结果显示算法能够在不到3s时间内识别一幅10000像素×10000像素图像中的港口,识别正确率为93.9%.     

利用同场景多幅图像进行图像降噪

提出一种利用同场景多幅图像作为输入来降低数码照片在高感光度下数码照片噪点的方法.该方法本质上基于按区块匹配加权平均值的方法.该方法在匹配区块的搜索过程中利用了计算机视觉中的追踪、变换等技术来减小搜索范围,从而大幅度降低了整个处理过程的时间复杂度,并且增加了匹配的准确度,满足了高分辨率图像在处理速度上的需求.此外,该方法...     

Image map correspondence for mobile robot self-location usingcomputer graphics

The use of computer graphics in estimating the position of an autonomous mobile robot navigating in an outdoor mountainous environment is discussed. A digital elevation map (DEM) of the area in which the robot is to navigate is given, and the robot is equipped with a camera that can be panned and tilted, a compass, and an altimeter. The position of the robot is estimated by establishing a correspondence between the images acquired by the camera on the robot (actual images) and the images generated from the DEM (predicted images) using computer graphics techniques. Features are extracted from the predicted images and the actual images that are used in establishing the correspondence. The features used are the horizon line contours (HLCs) in the images. To reduce the search space a constrained search paradigm is used. Geometric constraints help prune the search space significantly     

基于局部能量方差特性的数字图像取证

在数字图像取证领域,如何高效甄别自然图像和计算机生成图像受到越来越多的关注。文中介绍一种数字图像取证算法,通过傅里叶变换计算图像像素之间的相关性,并利用频域的局部抖动来区别照相机拍摄的自然图像和计算机生成的图像。同时提出对计算机生成图像采取插值处理和对自然图像进行缩放处理的反取证方法,并且分析这两种反取证技术的应对方法。与Gallagher等的方法相比,文中基于数字图像局部能量方差特性的取证准确率更高,且能有效抵抗图像的反取证。     

基于图像的室内虚拟环境的研究

基于图像的建模和绘制技术,提出了一个构造室内虚拟环境的完整方案,用户只需要输入少数照片,即可重建室内场景的全景图像,方案主要包括以下几点：首先由用户交互确定图像中的匹配象素,通过运动分析算法恢复整个场景的几何结构,然后,将原始图像变换至平面的参数坐标系,抽取纹理图像,并在参数空间对纹理图像进行拼接;最后生成场景的全景图像,算法对拍摄条件和设备没有苛刻要求,运算量较小,有较强的稳定性。     

Revealing digital fakery using multiresolution decomposition and higher order statistics

With the advance of digitization and digital processing techniques, digital images are now easy to create and manipulate, and leave no clues of artificial evidence. There are some known digital fakery for images, e.g., computer graphics (CGs) and digital forgeries. As valid records of natural world, natural images, i.e., photographic images, are no longer believable. In this paper, a detection scheme for natural images and fake images is proposed. Features are first extracted using multiresolution decomposition and higher order local autocorrelations (HLACs). The support vector machines (SVMs) are then used to differentiate the natural and fake images. Because the inner product between features can be obtained directly without computing features, it can be integrated into SVM, and the computation complexity is decreased. Experiments show that the proposed detection scheme is effective, demonstrating that the proposed statistical features can model the differences between natural images and fake images.     

Intrinsic Sensor Noise Features for Forensic Analysis on Scanners and Scanned Images

A large portion of digital images available today are acquired using digital cameras or scanners. While cameras provide digital reproduction of natural scenes, scanners are often used to capture hard-copy art in a more controlled environment. In this paper, new techniques for nonintrusive scanner forensics that utilize intrinsic sensor noise features are proposed to verify the source and integrity of digital scanned images. Scanning noise is analyzed from several aspects using only scanned image samples, including through image denoising, wavelet analysis, and neighborhood prediction, and then obtain statistical features from each characterization. Based on the proposed statistical features of scanning noise, a robust scanner identifier is constructed to determine the model/brand of the scanner used to capture a scanned image. Utilizing these noise features, we extend the scope of acquisition forensics to differentiating scanned images from camera-taken photographs and computer-generated graphics. The proposed noise features also enable tampering forensics to detect postprocessing operations on scanned images. Experimental results are presented to demonstrate the effectiveness of employing the proposed noise features for performing various forensic analysis on scanners and scanned images.      

Telidon graphics and applications

Telidon is essentially a computer graphics code which is very effective as the presentation level protocol for videotex, for which it was originally developed, teletext and other consumer- and business-oriented information systems. Its use of geometric primitives rather than the mosaic characters of its predecessors permits efficient digital storage and rapid transmission of detailed graphics. Display terminals can be built to display the images with different degrees of detail to suit the application.     

Character pattern extraction from documents with complex backgrounds

Recent remarkable progress in computer systems and printing devices has made it easier to produce printed documents with various designs. Text characters are often printed on colored backgrounds, and sometimes on complex backgrounds such as photographs, computer graphics, etc. Some methods have been developed for character pattern extraction from document images and scene images with complex backgrounds. However, the previous methods are suitable only for extracting rather large characters, and the processes often fail to extract small characters with thin strokes. This paper proposes a new method by which character patterns can be extracted from document images with complex backgrounds. The method is based on local multilevel thresholding and pixel labeling, and region growing. This framework is very useful for extracting character patterns from badly illuminated document images. The performance of extracting small character patterns has been improved by suppressing the influence of mixed-color pixels around character edges. Experimental results show that the method is capable of extracting very small character patterns from main text blocks in various documents, separating characters and complex backgrounds, as long as the thickness of the character strokes is more than about 1.5 pixels. Received July 23, 2001 / Accepted November 5, 2001     

Real reality

In its most basic form, computer graphics technology renders an image of the world from a model. Having refined techniques from vector graphics, computer graphics now includes improved methods to render realistic and informative visual images of models representing microcosms of interest. Computational technology includes mechanisms to compress, communicate and combine text, audio, graphics and video to provide a unified multimedia document. Users can now decide if they want to read a story, watch a video or combine information from multiple sources to create a personalized digital experience. So what future faces computer graphics and multimedia? Can we take the technology to still another level of reality? Let's assume we can expand the scope of computer graphics to produce and render a world model for information or entertainment that surpasses the visual, also representing sound, touch, smell and taste. Although seemingly far out now, I believe computer graphics and multimedia will combine and expand to make such a technology-real reality-possible. Virtual reality (VR) foreshadows this development. I believe real reality, or what may more accurately be called remote reality, lies just around the corner. Real reality will revolutionize our society in many ways. Unlike VR, real reality systems will let users experience and interact digitally with real environments using all the human senses. However, real reality experiences will remain free of time and space constraints. You will be able to experience a remote environment digitally at your convenience wherever you are     

Adaptive photograph retrieval method

Access to electronic books, electronic journals, and web portals, which may contain graphics (drawings or diagrams) and images, is now ubiquitous. However, users may have photographs that contain graphics or images and want to access an electronic database to retrieve this information. Hence, an effective photograph retrieval method is needed. Although many content-based retrieval methods have been developed for images and graphics, few are designed to retrieve graphics and images simultaneously. Moreover, existing graphics retrieval methods use contour-based rather than pixel-based approaches. Contour-based methods, which are concerned with lines or curves, are inappropriate for images. To retrieve graphics and images simultaneously, this work applies an adaptive retrieval method. The proposed method uses histograms of oriented gradient (HOG) as pixel-based features. However, the characteristics of graphics and images differ, and this affects feature extraction and retrieval accuracy. Thus, an adaptive method is proposed that selects different HOG-based features for retrieving graphics and images. Experimental results demonstrate the proposed method has high retrieval accuracy even under noisy conditions.     

一种自动立体显示器立体对比度和视区检测方法

提出了一种基于CCD摄像头的自动立体显示器立体对比度和视区检测方法。首先，运用Direct3D API设计的计算机图形显示在自动立体显示屏上。然后，用一台CCD摄像头代替人的双眼接受立体视图。最后，根据算法提取数字图像的特征参数来计算说明自动立体显示器显示效果的立体对比度，并获得观看自动立体显示器的左右眼视区分布。实验结果表明，此方法能很好地检测自动立体显示器的立体对比度和左右眼视区。