基于运动区域检测的会议视频清晰度增强处理

视频会议场景对视频增强的实时性有较高的要求.针对现有视频增强算法(如BM3D等)存在的耗时长的问题,基于变化区域检测提出一种基于运动区域检测的视频增强技术.对时序帧数据进行颜色空间转换,快速地将视频场景分为静止区域和运动区域,之后对静止区域进行时域降噪和视频增强.在视频帧集合的实验结果表明,该算法可以显著地增强图像纹理...     

一种基于Krawtchouk矩的视频水印算烦

针对现有视频水印算法很少考虑视频帧中确定的目标区域这一问题,提出一种基于Krawtchouk矩的视频水印算法(KVW).该算法利用Krawtchouk矩的目标区域提取能力,选取视频I帧中较为重要的信息区域作为水印的嵌入域.结合Krawtchouk低阶矩对剪切攻击的鲁棒性以及视频帧间相似度较高的特点,选择I帧和相邻P帧中相对稳定的低阶Krawtchouk矩作为最优矩集合.根据随机水印比特自适应地修改集合中的矩,并对差矢量进行Krawtchouk矩重构,通过将差值图像在空域迭加到I帧嵌入水印.水印检测时,首先计算受攻击I帧的Krawtchouk矩,以最优矩集合作为密钥,用相邻P帧Krawtchouk矩替代原始I帧数据提取水印,改善算法对原始数据的依赖性.实验结果表明,KVW算法在保证获得很好图像质量的同时,能够很好地抵抗帧剪切攻击以及常规的信号处理.     

基于融合差分的可变光强自适应目标识别算法

主要研究视频监控系统中运动目标检测算法,提出一种背景差分与帧间差分相融合的方法。该算法通过多次差分以及判决区域的相关运算划定背景区域和运动区域。同时参考相邻帧平均灰度信息更新背景帧以适应光线变化对判断造成的影响。在图像后处理中结合相关形态学算划分最终的运动目标。该算法可实现运动目标的快速准确定位和区域估算,实验表明该算法的时间复杂度和空间复杂度低,效果良好。     

面向HBP编码格式的立体视频B帧整帧丢失分层错误隐藏算法

针对分层B帧(HBP)编码格式的立体视频B帧整帧丢失的问题,该文分析了双视点视频中存在的视点间运动矢量相关性,提出一种分层错误隐藏算法。该算法与当前主流的方法有两大不同:一是该算法采用分级隐藏,根据B帧的重要性等级不同采用不同的错误隐藏方法;二是该算法考虑了相邻视点序列之间的宏块运动矢量相关性。实验表明,该算法的性能优于当前常用的H.264多视点视频整帧丢失错误隐藏方法。     

边缘检测与帧差法相融合的视频分割算法

常用的视频分割算法包括光流法、背景减除法和帧差法,但是3种算法容易受到计算量、环境噪声以及亮度突变等因素的影响,造成分割效果不理想。为了改善视频分割的质量,能够较好效果的提取到运动物体,提出一种将边缘检测与帧差法相融合的算法。该算法同时在两个方向进行。一是对相邻两帧图像进行边缘检测,将图像的边缘进行差分以得到运动物体的轮廓,为了连接轮廓中可能会出现的细小断点,对差分结果进行闭运算。二是根据设定的阈值,将相邻两帧图像的对应像素值转换为二值化数据,对二值化结果进行差分。最后综合闭运算与二值化差分结果,当数据发生突变时,即认为是运动物体部分。实验表明,该融合算法可以实时的检测到视频中的运动物体,效果较好。     

基于双通道卷积神经网络的视频目标移除取证算法

针对现有数字视频目标移除取证算法的伪造帧识别准确率低的问题,本文提出了一种基于双通道卷积神经网络的视频目标移除取证算法。该算法利用双通道结构,分别提取视频绝对帧差图像的RGB特征和噪声特征,并利用双线性池化对二者进行特征融合,而后通过分类层输出视频帧的分类结果,从而有效地识别经过篡改的视频帧。其中,RGB通道能够发现绝对帧差图像中不自然的篡改边界和对比度,噪声通道能够发现原始区域和篡改区域之间噪声的不一致性。此外,算法在网络前端增加了预处理层来放大篡改视频帧的伪造痕迹。实验结果显示,所提算法有效地提高了伪造视频帧的识别准确率,且相对于传统的单通道网络结构,双通道特征融合的方式取得了更好的检测性能。      

图像和视频亮度的自动调整

 对曝光不足的图像和视频进行亮度调整具有重要的理论研究意义和实际应用价值,本文提出一种基于梯度域操作的图像和视频亮度自动调整算法.对于静态图像,算法首先将图像分割为不同的亮度区域;然后分别计算各区域的亮度调整算子;最后通过求解一个梯度约束方程得到结果图像.我们进而将该算法延伸到视频,首先选取若干关键帧并使用上述图像亮度调整算法进行处理;然后对非关键帧进行分割并通过光流算法确定非关键帧上的分割区域与前后关键帧区域的对应关系;最后利用对应关系通过关键帧区域的亮度调整算子以及调整后的亮度指导非关键帧上各区域的亮度调整,并生成结果视频序列.本文算法可以有效处理空间和时间上曝光不足和不均的图像和视频,并能够较好地保持图像、视频的细节纹理信息,实验结果表明了算法的有效性.     

基于整数小波变换的彩色视频水印算法

提出了一种基于整数小波变换的视频水印技术.算法首先对水印进行混沌加密和Arnold置乱处理和借助密钥选取r帧视频;其次对选取视频帧的每一通道进行互不重叠的8×8分块和对选取的每一分块进行1级整数小波变换;最后根据视觉掩蔽特性来自适应调整两相邻块对应高频子带均值之间的大小关系以嵌入水印.实验表明,该算法实现简单,具有较好的透明性和鲁棒性.     

基于多规则小波变换的视频水印加密算法研究

通过对视频嵌入水印的安全性和鲁棒性的分析,采用了一种基于多规则小波变换的视频水印嵌入与提取算法.该算法首先对水印图像进行置乱加密增强其安全性,其次对视频帧和水印图像分别进行多层小波变换,最后根据不同的小波系数进行多规则水印嵌入.算法不仅充分利用了小波变换的多分辨特性,而且兼顾了水印的不可感知性和视频帧的鲁棒性.实验结果表明,该算法对高斯噪声、几何失真和压缩等具有良好的安全性和鲁棒性.     

基于非局部均值滤波的视频图像去雨方法

提出了一种有效的基于非局部均值滤波的去雨方法。首先利用雨的空间特征检测出视频帧中的雨线区域,并对其进行标记。然后针对当前帧的被标记的像素块使用非雨块匹配算法,用于相邻的帧之间以找出和有雨像素区域相似的块。最后使用时空非局部均值滤波对块中的雨区进行重构,达到去除雨滴的目的。实验结果表明,比起常规算法,文中提出的算法可以更有效地去除雨线,恢复出更高质量的图像。     

基于CV模型的SAR图像机场感兴趣区域检测

高分辨率POLSAR图像的机场感兴趣区域(Region of interest,ROI)的自动提取是自动目标识别(AutomaticTarget Recognition,ATR)系统的任务之一,也是准确识别分类飞机等小目标的基础。针对全极化合成孔径雷达(POLSAR)图像极化相干的特点,提出一种融合提取方法:先使用J.S.Lee Sigma filter滤波,再利用Shannon-Entropy理论提高ROI和背景对比度,采用基于CV模型的方法分割图像,然后对分割得到的图像进行形态学等图像处理,最终得到机场ROI。实验结果表明,该方法具有分割界限清晰、定位准确的优点。     

Fractal coding of video sequence using circular prediction mappingand noncontractive interframe mapping

We propose a novel algorithm for fractal video sequence coding, based on the circular prediction mapping and the noncontractive interframe mapping. The proposed algorithm can effectively exploit the temporal correlation in real image sequences, since each range block is approximated by the domain block in the adjacent frame, which is of the same size as the range block. The computer simulation results demonstrate that the proposed algorithm provides very promising performance at low bit rate, ranging from 40-250 kbyte/s.     

HDR视频映射算法研究

基于对传统伽马指数函数、及最新Dolby PQ函数的深入研究和分析,针对采用Dolby PQ函数编码的HDR视频节目内容,提出直接将编码亮度在范围内的视频图像像素映射至电视机屏幕进行保真显示、而采用亮度压缩方式将其他高亮和低亮视频图像像素映射至电视机屏幕进行显示的HDR视频映射算法;试验证明能够将HDR视频源内PQ函数编码的像素亮度映射至电视机屏幕显示亮度的动态范围之内,保证视频源图像内容能够较真实的在电视机屏幕上显示,避免了HDR视频图像显示时出现内容丢失;以及算法且易于实现、能够快速进行商业应用.     

基于分层色调映射的LED背光调制算法

为了在降低液晶显示器背光功耗的同时能够保持图像质量,提出了基于分层色调映射的LED背光调制算法.利用低通滤波对图像进行分层,通过亮度对数映射函数把低频部分映射到低动态范围,再与增益后的高频部分相结合为输出图像.将输出图像最大灰阶能够增加的数值作为LED背光因子降低值,采用动态背光缩放技术,降低背光强度值,并提高液晶透光...     

HDR tone mapping algorithm based on difference compression with adaptive reference values

Tone mapping remains a challenging problem since tone mapping operators need to produce high perceptual quality under all conditions. In this paper, we propose a new local tone mapping method based on difference compression with adaptive reference values, which can effectively reproduce the details of bright and shadow regions. We also use a global tone mapping method and blend the output images produced by the global and local methods based on objective quality metrics. To quantitatively measure output images, we developed a new objective quality metric for the tone mapped images. The proposed detailness metric measures detail loss in the bright and shadow regions, and shows good correlations with subjective quality. We combined this metric with the recently proposed tone mapped image quality index (TMQI) that may not sufficiently reflect the amount of local detail loss. The experiments show that the proposed algorithm provides better perceptual quality than existing methods.     

Human centered perceptual adaptation for video coding

Traditional visual saliency based video compression methods try to encode the image with higher quality in the region of saliency. However, the saliency feature changes according to persons, viewpoints, and distances. In this paper, we propose to apply a technique of human centered perceptual computation to improve video coding in the region of human centered perception. To detect the region of interest (ROI) of human body, upper body, frontal face, and profile face, we construct Harr and histogram of oriented gradients features based combo of detectors to analyze a video in the first frame (intra-frame). From the second frame (inter-frame) onward, the optical flow image is computed in the ROI area of the first frame. The optical flow in human centered ROI is then used for macroblock (MB) quantization adjustment in H.264/AVC. For each MB, the quantization parameter (QP) is optimized with density value of optical flow image. The QP optimization process is based on a MB mapping model, which can be calculated by an inverse of the inverse tangent function. The Lagrange multiplier in the rate distortion optimization is also adapted so that the MB distortion at human centered region is minimized. We apply our technique to the H.264 video encoder to improve coding visual quality. By evaluating our scheme with the H.264 reference software, our results show that the proposed algorithm can improve the visual quality of ROI by about 1.01 dB while preserving coding efficiency.     

Digital based calibration technique for continuous-time bandpass sigma-delta analog-to-digital converters

In this paper, a calibration technique for Noise Transfer Function (NTF) optimization of Continuous-Time Bandpass Sigma Delta (CT BP ΣΔ) modulators is presented. The proposed technique employs a test tone applied at the input of the quantizer to evaluate the noise transfer function of the Analog-to-Digital Converter (ADC) using the capabilities of the Digital Signal Processing (DSP) platform usually available in mixed-mode systems. Once the ADC output bit stream is captured, necessary information to generate the control signals to tune the ADC parameters for best Signal-to-Quantization Noise Ratio (SQNR) performance is extracted via an LMS software-based algorithm. Simulation results show that notch frequency of the NTF due to process variations and temperature tolerances can be tuned using the proposed methodology. The proposed global calibration approach can be used during the system start-up and the idle system time. The proposed approach uses a single in-band calibration tone, but it can be expanded using out-of band test tones for background calibration schemes.     

3D视频生成与编码的时间一致性深度图估计

In this paper, we propose a new algorithm for temporally consistent depth map estimation to generate three-dimensional video. The proposed algorithm adaptively computes the matching cost using a temporal weighting function, which is obtained by block-based moving object detection and motion estima-tion with variable block sizes. Experimental results show that the proposed algorithm im-proves the temporal consistency of the depth video and reduces by about 38% both the flic-kering artefact in the synthesized view and the number of coding bits for depth video coding.     

Region-of-interest based rate control for UAV video coding

To meet the requirement of high-quality transmission of videos captured by unmanned aerial vehicles (UAV) with low bandwidth, a novel rate control (RC) scheme based on region-of-interest (ROI) is proposed. First, the ROI information is sent to the encoder with the latest high efficient video coding (HEVC) standard to generate an ROI map. Then, by using the ROI map, bit allocation methods are developed at frame level and large coding unit (LCU) level, to avoid inaccurate bit allocation produced by camera movement. At last, by using a better robustness R-λ model, the quantization parameter (QP) for each LCU is calculated. The experimental results show that the proposed RC method can get a lower bitrate error and a higher quality for reconstructed video by choosing appropriate pixel weight on the HEVC platform.     

A Kalman filtering approach to stochastic global andregion-of-interest tomography

We define two forms of stochastic tomography. In global tomography, the goal is to reconstruct an object from noisy observations of all of its projections. In region-of-interest (ROI) tomography, the goal is to reconstruct a small portion of an object (an ROI) from noisy observations of its projections densely sampled in and near the ROI and sparsely sampled away from the ROI. We solve both problems by expanding the object and its projections in a circular harmonic (Fourier) series in the angular variable so that the Radon transform becomes Abel transforms of integer orders applied to the harmonics. The algorithm has three major components. First, we fit state-space models to each order of Abel transform and thus represent the Radon transform operation as a parallel bank of systems, each of which computes the appropriate Abel transform of a circular harmonic. A variable transformation here allows either the global or ROI problem to be solved. Second, the object harmonics are modeled as a Brownian branch. This is a two-point boundary value system, which is Markovianized into a form suitable for the Kalman filter. Finally, a parallel bank of Kalman smoothing filters independently estimates each circular harmonic from the noisy projection data. Numerical examples illustrate the proposed procedure.