一种空域DCT与时域DWT相结合的鲁棒视频数字水印算法

为了保护数字视频知识产权,提出一种基于视频序列空域DCT变换和时域DWT变换的数字水印算法。首先在HSV空间上对原始视频每帧做DCT变换,从中提取出亮度分量的低频系数,并对其做时间轴上的DWT得到序列的高通成份和低通成份。对水印图像做了基于混沌理论的置乱加密,通过DWT将彩色水印图像的高、低频信息多分辨地嵌入宿主视频序列中。在水印重构过程中不需调用原始视频。对所提出的视频水印算法进行了较充分的攻击测试实验,实验结果表明了本文算法具有较强的鲁棒性。     

一种新的能量均值音频水印算法

高度鲁棒数字音频水印算法研究是一项富有挑战性的工作。为了在数字音频水印技术中提高抗去同步攻击,文章以能量均值、特征点为理论基础,提出了一种新颖的鲁棒性数字音频水印算法。该算法选取数字音频的局部能量峰值点作为特征,提取稳定的特征点;以特征点为标记,对特征点后的区域进行DWT,然后对低频系数分段,利用能量均值和音频幅值成正比的方法,将水印嵌入到原始音频的小波域中。水印提取时无需原始图像。仿真实验表明,所提出的算法对常规信号处理和去同步攻击均具有较好的鲁棒性。     

基于Android智能手机的彩色图像盲数字水印算法

针对智能手机上的图像版权保护问题,提出了一种适用于Android系统的彩色图像盲水印算法。算法根据DCT系数和图像灰度值之间的线性关系直接在空域中修改DCT系数。这种方法无需进行DCT变换和反DCT变换,可大幅度降低计算量。此外,该算法提取水印时不需要原始载体图像,能够实现盲提取。在Android手机上对该算法进行了大量实验,实验结果表明,提出的算法具有良好的透明性和鲁棒性。     

基于彩色分量的数字图像水印

提出了一种基于彩色图像色差分量离散余弦变换(DCT)域下的数字图像水印算法.该算法通过修改两色差分量的DCT系数,将水印信号埋植到图像中,而在水印信息检测时,不需要原始图像以及其他额外的数据.经实验测试,该算法可以抵抗诸如JPEG压缩、低通滤波、降采样、放大和缩小以及裁剪等大多数图像处理方法的攻击,具有很高的橹棒性和不可见性.     

复杂背景下的红外小目标检测

针对复杂背景红外序列中小目标检测问题,提出了基于形态学Top-hat算子和运动连续性的目标检测算法。形态学中的Top-hat算子是一种极好的高通滤波算子,开Top-hat算子能检测图像中的峰,而闭Top-hat算子则能检测图像中的谷。通过对Top-hat算子选择合适的结构元,就可以将候选的目标从复杂的背景中提取出来,然后利用序列图像中运动目标的连续性和轨迹的一致性筛选出真正的目标。试验结果表明,该方法能有效抑制背景噪声、检测并跟踪红外小目标。     

基于MeanShift和Harris算子圆网印花机对花检测的研究与设计

为了实现基于智能相机的圆网印花自动对花系统,本文提出了基于均值漂移(MeanShift)算法的彩色印花图案分割技术和基于Harris角点检测的块匹配算法。将扩展形式的均值漂移算法用于印花图案的分割,实验证明该算法能对印花图像进行良好的分割。把已分割标准图像的各套色区域提取出来,采用Harris算子进行特征点检测,并以这些特征点为中心,选定标准匹配块,在处理好的实时采集的图像中找到最佳匹配块,计算对花误差。通过仿真和实验验证算法是可行性的,为实现在线对花检测闭环控制打下基础。     

融合多高斯混合模型与Graph Cuts优化技术的目标自动检测方法

本文将时城信息与空域信息融合,利用Graph Cuts全局最优特性,通过自适应的信息融合策略,提取运动目标.在自动化跟踪系统中,从图像序列提取运动目标信息,是进行目标检测与跟踪的前提.目前,目标信息提取方法包括对视频图像序列的时域和空域进行分析.利用时域信息,可以比较好地提取出目标的运动信息,区分出前景和背景.而把利用...     

基于霍夫变换的射波刀等中心误差胶片分析算法

目的 提出一种基于霍夫变换(HT)的新算法提高射波刀自动质量保证(AQA)测试胶片影像分析的准确性与稳定性,并探讨胶片图像的扫描分辨率对测试结果的影响。方法 获取9对胶片对AQA模体进行分析测试,首先利用中值滤波对灰度化后的胶片影像预处理,去除噪声干扰;再使用全局阈值对图像进行二值化分割,对分割后的图像进行边缘检测并利用HT提取胶片边缘直线,将胶片图像变换至正确位置;最后利用边缘检测和HT提取出影像中射野投影圆和钨球投影圆的圆心,通过分析同心度最终得到AQA测试的误差分析结果。结果 所有样本分别使用本算法与原软件算法所得等中心误差结果差异无统计学意义(P>0.05),其标准差差异有统计学意义(P=0.027);表明本算法在保证了胶片分析准确性的同时具有更好的稳定性。两种方法均不能通过采用分辨率更高的胶片影像来提高分析结果的准确性和稳定性。结论 本算法排除了胶片扫描摆位误差造成的干扰,为射波刀系统AQA工作提供了一种更稳定的途径。     

基于双边滤波的POCS超分辨率图像序列重建算法

针对传统凸集投影(POCS)超分辨率图像序列重建算法使用高斯滤波器来估计点扩散函数(PSF)导致边缘模糊的现象,本文采用双边滤波器来估计PSF,双边滤波方法是将高斯函数和图像亮度信息相乘,优化后的权系数再与图像作卷积,使重建后的图像边缘得到很好保持。运动估计是POCS超分辨率图像序列重建算法的关键技术,本文选择结合图像金字塔的光流估计对图像序列进行配准,得到更加精确的估计结果。实验表明,可以使重建图像取得良好的视觉效果。     

基于多传感器决策级融合的远距离目标检测

本文针对可见光和红外热图像序列中远距离目标检测,提出了一种基于决策级融合的目标检测方法。该方法首先是通过帧间差累积和提取局部灰度信息的方法对各传感器图像进行目标检测处理;接着采用“与”逻辑对各传感器的目标检测结果进行融合,除去部分冗余信息;然后在各传感器图像中提取融合检测结果中各候选区域的多个图像特征作为进一步消除冗余信息的证据;最后采用D-S证据理论对各候选区域进行基于多特征的目标融合识别处理并将识别的结果作为整个系统最终的目标检测输出。实验结果证明了本文方法的有效性。     

基于三维投影的视频序列静态全景合成算法

视频序列静态全景合成技术是视频图像分析的关键技术。本文提出了一种基于三维投影的视频序列静态全景合成算法,该算法通过引入三维投影原理,将视频序列中各帧图像依次投影到全景图像平面,推导出在同一三维坐标下各帧图像与全景图像之间的变换关系,并采用各帧图像间的运动参数联合生成全景图像。实验结果表明,该方法能够生成较高质量的全景图。     

Performance evaluation of automatic anatomy segmentation algorithm on repeat or four-dimensional computed tomography images using deformable image registration method

PURPOSE: Auto-propagation of anatomic regions of interest from the planning computed tomography (CT) scan to the daily CT is an essential step in image-guided adaptive radiotherapy. The goal of this study was to quantitatively evaluate the performance of the algorithm in typical clinical applications. METHODS AND MATERIALS: We had previously adopted an image intensity-based deformable registration algorithm to find the correspondence between two images. In the present study, the regions of interest delineated on the planning CT image were mapped onto daily CT or four-dimensional CT images using the same transformation. Postprocessing methods, such as boundary smoothing and modification, were used to enhance the robustness of the algorithm. Auto-propagated contours for 8 head-and-neck cancer patients with a total of 100 repeat CT scans, 1 prostate patient with 24 repeat CT scans, and 9 lung cancer patients with a total of 90 four-dimensional CT images were evaluated against physician-drawn contours and physician-modified deformed contours using the volume overlap index and mean absolute surface-to-surface distance. RESULTS: The deformed contours were reasonably well matched with the daily anatomy on the repeat CT images. The volume overlap index and mean absolute surface-to-surface distance was 83% and 1.3 mm, respectively, compared with the independently drawn contours. Better agreement (>97% and <0.4 mm) was achieved if the physician was only asked to correct the deformed contours. The algorithm was also robust in the presence of random noise in the image. CONCLUSION: The deformable algorithm might be an effective method to propagate the planning regions of interest to subsequent CT images of changed anatomy, although a final review by physicians is highly recommended.     

基于小波变换极大模的多模医学图像融合

多模态医学图像融合由于其对医学临床诊断的意义已引起广泛的关注,基于图像边缘特性的融合方法逐渐成为研究的重点。本文提出了一种基于离散二进小波变换的多尺度边缘检测和图像融合的方法,实现了特征级图像融合。不同于以往的从极大模值点直接重建图像,本文的算法利用极大模值点建立有效的融合规则,然后从融合的小波系数重构信号。融合图像的交互信息和峰值信噪比等检测指标表明此方法优于传统融合算法。     

Near infrared photonic finger imager for prostate cancer screening

A portable rectal near infrared (NIR) scanning polarization imaging unit with an optical fiber-based rectal probe, designated as a Photonic Finger (PF), was designed, developed, built and tested. PF was used to image and locate the three dimensional (3D) positions of abnormal prostate tissue embedded inside normal prostate tissue. An inverse image reconstruction algorithm, namely Optical Tomography using Independent Component Analysis (OPTICA) was developed to unmix the signal from targets (cancerous tissue) embedded in a turbid media (normal tissue) in the backscattering imaging geometry. The Photonic Finger combined with OPTICA was ex vivo tested to characterize different target(s) inside different tissue medium, including cancerous prostate tissue embedded inside large pieces of normal tissue. This new developed instrument, Photonic Finger, may provide an alternative imaging technique, which is accurate, of high spatial resolution and non-or-less invasive for prostate cancers screening.     

基于非采样Contourlet变换和Wiener滤波的图像去噪

提出了一种基于非采样Contourlet变换与Wiener滤波相结合的图像去噪算法。非抽样Contourlet变换可以实现多分辨、局部、尤其是多方向图像表示,且具有平移不变性,避免了去噪过程中出现的伪Gibbs现象 而Wiener滤波在最小均方误差意义上是对图像的最优估计。该算法结合Contourlet变换和Wiener滤波各自的优点,首先采用非采样Contourlet变换对含噪图像进行多尺度、多方向分解,得到低频子带系数和各带通方向子带系数 然后在各子带图像上进行Wiener滤波 最后经过非采样Contourlet逆变换得到去噪估计图像。该方法应用于peppers图片去噪,结果图像峰值信噪比（PSNR）增加为15.6775,最小均方误差（MSE）减小为1749,好于Wiener去噪（PSNR为13.7618,MSE为2549）和小波与Wiener滤波相结合去噪（PSNR为14.0662,MSE为2734）。实验结果表明此方法提高了图像的峰值信噪比、减小了均方误差。     

Optimal stochastic correction strategies for rigid-body target motion

PURPOSE: To derive optimal correction strategies for setup errors, including the uncertainty in their measurement, and to analyze their impact on treatment margins. METHODS AND MATERIALS: New concepts like image-guided radiotherapy aim to provide an increasing amount of targeting information during treatment. Future treatment devices incorporating imaging capabilities will facilitate frequent correction of treatment setup errors. It is, therefore, possible to design new correction protocols that reduce not only systematic but also random setup errors. A novel, very general approach to developing optimal correction strategies in the presence of measurement uncertainties is derived from linear systems theory. In the simplest approach, the state variable of the system, which represents the patient, is the spatial displacement of the center-of-mass of the clinical target volume with respect to the planning CT. This displacement is the sum of a systematic and a random component. Uncertainties in the measured value of the state variable due to the measurement process, image processing technique, or organ deformation are naturally incorporated into a linear system. The true value of the displacement can be estimated from the noisy measurements with a stochastic filter (Kalman filter). These estimates provide an optimal control law for the system and therefore optimal values for the setup corrections. In the case of unknown systematic and random error variances, an adaptive version of the filter was implemented. The statistical properties of the filter were investigated by performing simulations of the state space model and assessed for individual patients and a large patient population subject to different action criteria. RESULTS: Over a patient population, the corrections by the Kalman filter estimates are always advantageous compared with the corrections by the measured values themselves. For a small percentage of individual patients, however, the Kalman corrections worsen the results. For large measurement error, the residual standard deviation of the random setup errors can be reduced by approximately 28% for over 90% of the patients. The uncertainty in the measured value impairs the ability to completely account for uncertainties. CONCLUSIONS: The Kalman estimates provide an effective means to perform daily setup corrections in the presence of measurement errors. The linear system approach is very versatile and can be extended to more general state variables.