A MV-Based Steganographic Algorithm for H.264/AVC without Distortion

H.264/AVC video is one of the most popular multimedia and has been widely used as the carriers of video steganography. In this paper, a novel motion vector (MV) based steganographic algorithm is proposed for the H.264/AVC compressed video without distortion. Four modules are introduced to eliminate the distortion caused by the modifications of motion vectors and guarantee the security of the algorithm. In the embedding block, the motion vector space encoding is used to embed a (2n+1)-ary notational number into an n-dimension vector composed of motion vectors generated from the selection block. Scrambling is adopted to disturb the order of steganographic carriers to improve the randomness of the carrier before the operation of embedding. The re-motion compensation (re-MC) block will re-construct the macroblock (MB) whose motion vectors have been modified by embedding block. System block plays the role of the generator for chaotic sequences and encryptor for secret data. Experimental results demonstrate that our proposed algorithm can achieve high embedding capacity without stego video visual quality distortion, it also presents good undetectability for existing MV-based steganalysis feature. Performance comparisons with other existing algorithms are provided to demonstrate the superiority of the proposed algorithm.     

基于H.264的自适应可伸缩编码研究

为了更好地适应网络及终端的多样性,本文针对基于H.264的可伸缩编码,提出了一种基于运动区域的自适应可伸缩编码的优化方案.该方案根据基本层的运动信息及编码模式自动提取图像的运动感兴趣区域,并以独立片的形式对其进行时间,空间和质量上的可伸缩编码,实现选择性增强.实验结果表明,该方案不仅能大幅降低编码复杂度,而且使增强层码流集中包含运动区域信息,从而提高运动区域的重建质量及整幅图像的主观质量.     

Motion estimation and compensation based on almost shift-invariant wavelet transform for image sequence coding

There has been rapid progress in the application of wavelet transforms to image and image sequence compression. The standard discrete wavelet transform lacks transition invariance in image decomposition which will affect the accuracy of motion estimation from the decomposed subimages in video coding. In this article, we present a study of applying an almost shift-invariant wavelet transform with “oversampled frames” to image sequence compression. With minimal oversampling and biorthogonal spline wavelets in the almost shift-invariant wavelet transform, motion vectors can be more accurately estimated, contributing toward fewer prediction errors in comparison to those obtained with the standard discrete wavelet transform. Thus, an improved compression ratio can be obtained. We present two new algorithms, the full-motion oversampling algorithm (FMOS) and the reduced search multiresolution motion estimation algorithm (MRME), for estimating motion fields at different scales and in different subimages. In the latter, motion vectors at a higher resolution are approximated by the motion vector estimates at a lower resolution through proper scaling. Experiments were performed on three video sequences with a variety of motions including slow, fast, and zooming. Our results have shown that both algorithms, FMOS and MRME, using the almost shift-invariant oversampled frame wavelet transform have reduced prediction errors and enhanced the compression performance in terms of peak-signal-to-noise ratio (PSNR) for the same bit rate when compared to the existing full motion standard algorithm. © 1998 John Wiley & Sons, Inc. Int J Imaging Syst Technol, 9, 214–229, 1998     

Optical flow-based motion compensation algorithm for very low-bit-rate video coding

In this article, we propose an efficient compression algorithm for very low-bit-rate video applications. The algorithm is based on (a) an optical-flow motion estimation to achieve more accurate motion prediction fields; (b) discrete cosine transformation (DCT) coding of the motion vectors from the optical-flow estimation to reduce the motion overheads; and (c) an adaptive threshold technique to match optical flow motion prediction and minimize the residual errors. Unlike the classic block-matching based DCT video coding schemes in MPEG-1/2 and H.261/3, the proposed algorithm uses optical flow for motion compensation and the DCT is applied to the optical flow field instead of predictive errors. Thresholding techniques are used to treat different regions to complement optical flow technique and to efficiently code residual data. While maintaining a comparable peak signal-to-noise ratio (PSNR) and computational complexity with that of ITU-T H.263/TMN5, the reconstructed video frames of the proposed coder are free of annoying blocking artifacts, and hence visually much more pleasant. The computer simulation are conducted to show the feasibility and effectiveness of the algorithm. Results at 11 kbps are presented which can be used for videophone applications in the existing public switched telephone network (PSTN). © 1998 John Wiley & Sons, Inc. Int J Imaging Syst Technol, 9, 230–237, 1998     

A probabilistic approach for video stabilisation in compressed domain

Machine vision systems, which are being extensively used for intelligent transportation applications, such as traffic monitoring and automatic navigation, suffer from image instability caused by environment unstable conditions. On the other hand, by increasing the use of home video cameras which sometimes need to remove unwanted camera movement, which is created by cameraman shaking hands, video stabilisation algorithms are being considered. The video stabilisation process consists of three essential phases: global motion estimation, intentional motion estimation and motion compensation. Motion estimation process is the main time consuming part of global motion estimation phase. Using motion vectors extracted directly from MPEG compressed video, instead of any other special feature, can increase the algorithm generality. In addition, it provides the facility for integrating video stabilisation and video compression subsystems and removing the block matching phase from video stabilisation procedure. Elimination of any iterative outlier removal preprocessing and adaptive selection of motion vectors has increased speed of the algorithm. Although deterministic approaches are faster than the related probabilistic methods, they have essential problems in escaping from local optima. For this purpose, particle filters, the ability of which is considerable when submitted to non-linear systems with non-Gaussian noises, are utilised. Setting the parameters of the particle filter using a fuzzy control system reduces the incorrect intentional camera motion removal. The proposed method is simulated and applied to video stabilisation problem and its high performance on various video sequences is demonstrated.     

Optimal weighed Holoentropy for video compression: an advanced HEVC

ABSTRACT

In recent times, the applications of multimedia are rising in a greedy mode and hence the amount of video transactions is also increasing exponentially. This has shouted great demands on effective models on video encoding and also for reducing the transmission channel congestion. This research work introduces a managing technique termed weighted encoding for High-Efficiency Video Coding (HEVC). HEVC, also termed as MPEG-H Part 2 and H.265 is a video compression standard that is widely utilized AVC (H.264 or MPEG-4 Part 10). When compared to AVC, HEVC grants double the ratio of data compression at a similar level of quality of the video or considerably enhanced video quality at a similar bit rate. This work intends to optimize the weight that adopted in HEVC for encoding. For this, this paper proposes a new Iterative based propagation update in the water wave Optimization Algorithm (IPU-WWO), which is the improved form of Water wave Optimization (WWO). The performance of proposed IPU-WWO is compared over other conventional methods like Artificial Bee Colony (ABC), Firefly (FF), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) with respect to Peak Signal to Noise Ratio (PSNR). By doing the encoding process, it minimizes the video size with perceptually better quality video or PSNR.     

Single-shot blind uniform motion deblurring with ringing reduction

In this paper, we have proposed a blind motion deblurring algorithm that comprises the estimation of the motion blur parameters (length and angle) in a modified cepstrum domain with a blind no-reference image spatial quality evaluator (BRISQUE) used for the tuning of point spread function (PSF) parameters. Ringing artifacts are generated during the deblurring process. In this paper, the modified R–L (Richardson–Lucy) algorithm with weight calculation based on graphcut is presented to obtain good estimates of the unblurred image with ringing reduction. The method involves the selection of different weights for edges and smooth regions such that the ringing effect over R–L iterations can be reduced. A newly proposed method has been tested on various natural images with a motion blur of different length and degrees. A comparison with state-of-the-art methods proves that the proposed technique achieved better results in terms of different quality measures such as SSIM, FSIM and PSNR and can be greatly beneficial for deblurring purpose.     

Block‐based recursive motion filtering for preserving true motion vectors in time‐varying texture objects

True motion estimation is necessary for deinterlacing, frame‐rate conversion, and film judder compensation. There have been several block‐based approaches to find true motion vectors by tracing minimum sum‐of‐absolute‐difference values by considering spatial and temporal consistency. However, the algorithms cannot find robust motion vectors when the texture of objects is changed. To find the robust motion vectors in the region, a recursive vector selection scheme and an adaptive weighting parameter are proposed. Previous frame vectors are recursively averaged to be utilized for motion error region. The weighting parameter controls fidelity to input vectors and the recursively averaged ones, where the input vectors come from the conventional estimators. If the input vectors are not reliable, then the mean vectors of the previous frame are used for temporal consistency. Experimental results show more robust motion vectors than those of the conventional methods in time‐varying texture objects. © 2008 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 18, 265–275, 2008; Published online in Wiley InterScience (www.interscience.wiley.com).     

Reversible Data Hiding Based on Run-Level Coding in H.264/AVC Video Streams

This paper presents a reversible data hiding (RDH) method, which is designed by combining histogram modification (HM) with run-level coding in H.264/advanced video coding (AVC). In this scheme, the run-level is changed for embedding data into H.264/AVC video sequences. In order to guarantee the reversibility of the proposed scheme, the last nonzero quantized discrete cosine transform (DCT) coefficients in embeddable 4×4 blocks are shifted by the technology of histogram modification. The proposed scheme is realized after quantization and before entropy coding of H.264/AVC compression standard. Therefore, the embedded information can be correctly extracted at the decoding side. Peak-signal-noise-to-ratio (PSNR) and Structure similarity index (SSIM), embedding payload and bit-rate variation are exploited to measure the performance of the proposed scheme. Experimental results have shown that the proposed scheme leads to less SSIM variation and bit-rate increase.     

Contrast limited fuzzy adaptive histogram equalization for enhancement of brain images

Contrast limited fuzzy adaptive histogram equalization (CLFAHE) is proposed to improve the contrast of MRI Brain images. The proposed method consists of three stages. First, the gray level intensities are transformed into membership plane and membership plane is modified with Contrast intensification operator. In the second stage, the contrast limited adaptive histogram equalization is applied to the modified membership plane to prevent excessive enhancement in contrast by preserving the original brightness. Finally, membership plane is mapped back to the gray level intensities. The performance of proposed method is evaluated and compared with the existing methods in terms of qualitative measures such as entropy, PSNR, AMBE, and FSIM. The proposed method provides enhanced results by giving better contrast enhancement and preserving the local information of the original image. © 2017 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 27, 98–103, 2017     

H.264/AVC baseline profile to MPEG‐4 visual simple profile transcoding to reduce the spatial resolution

In this study, we propose a heterogeneous transcoding method of converting an H.264/Advanced video coding (AVC) Baseline profile (BP) video bitstream into an MPEG‐4 Visual simple profile (VSP) video bitstream. The proposed method reduces the spatial resolution for mobile terminals, which support only low resolution video bitstreams. When the H.264/AVC BP video bitstream is transformed into the MPEG‐4 VSP video bitstream, the conversions between the H.264/AVC BP block types and the MPEG‐4 VSP block types are performed by analyzing the macroblocks (MBs) conversion probability and calculating the difference values of motion vector. The proposed transcoding method runs on average 5.5 times faster than the cascaded transcoding methods, for a degradation of the PSNR (peak‐signal‐to ratio) of less than 0.5 dB. © 2006 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 16, 24–33, 2006     

支持ROI优先编码策略的自适应码率控制算法

在低码率视频通信中,感兴趣区(ROI)优先编码策略有助于图像主观质量的提高。本文提出了一种简单有效的ROI提取方法,并根据图像复杂度和运动信息给ROI和非感兴趣区(NROI)分别分配码流。对于ROI的编码范畴,文中推导出了高低码率的判断准则,使算法可以自适应地选择码率模型,减少了码率控制误差。另外,本文采用的宏块层编码顺序方案提高了图像的客观质量。实验结果表明,与TMN7和TMN8的算法相比,本文算法能将码率更稳定地控制在目标码率附近,减少了跳帧;图像的客观和主观质量都有了明显的提高。     

一种基于HVS特性的视频质量评测方法

本文针对视频质量的评测应用,对传统峰值信噪比(PSNR)算法加以改进.通过在视频帧内图像和帧间图像的处理过程中引入人眼视觉系统(HVS)的主要特性,克服传统PSNR算法在序列质量检测应用方面的缺陷.方法在帧内图像处理上利用人眼对边缘轮廓失真具有较强敏感性的特点,设计了基于图像边缘的检测方案以提高对典型空域失真的检测性能;在帧间图像处理上,通过测量帧间时域能量的变化,获得序列在时域轴上的典型特征,并据此对空域检测结果进行修正.通过上述改进,算法能在保持传统PSNR算法简易性的同时,提升其检测结果与主观感受的相关性;同时算法的计算量并不复杂,易于在检测设备中实现系统集成     

巴旦木壳基生物炭的制备及其吸附性能表征

为控制环境污染领域提供新材料,分别在300、400和500℃条件下制备了巴旦木壳(BC)和干炒巴旦木壳(BCF)生物炭,并用不同浓度的HCl和NaOH对生物炭进行了改性。用国标法表征了生物炭的真密度、灰分、钙镁含量、pH值、焦糖脱色率、亚甲基蓝吸附量、碘吸附值及比表面积等基本性质,并对溶液中Pb²⁺和Zn²⁺的吸附特性进行了研究。实验结果显示,随着炭化温度的升高,两种生物炭的产率降低,灰分、钙镁含量、真密度、比表面积、孔体积、碘吸附值和pH值增加;BC500和BCF500的比表面积分别达到了199.97和295.44m²/g。BCF的灰分明显高于BC;酸碱及其浓度对不同参数产生的影响不一致。400℃碳化的两种生物炭的亚甲基蓝吸附值较高,酸碱改性后吸附值均增高;高温热解有利于制备碘吸附值高的生物炭,碱改性能提高碘吸附值,BC500和BCF500及其碱改性产物的碘吸附值达到330mg/g以上;两种生物炭及其改性产物的焦糖脱色率变化没有明显规律;高浓度酸碱改性显著降低了高温制备的BC和BCF的Pb吸附量;酸改性降低了、碱改性提高了两种生物炭的Zn吸附量。总之,两种巴旦木壳生物炭对不同物质的吸附特性不同,建议根据污染物的种类选择不同的生物炭制备工艺和改性剂。     

Image motion estimation by clustering

Image motion is estimated by matching feature “interest” points in different frames of video image sequences. The matching is based on local similarity of the displacement vectors. Clustering in the displacement vector space is used to determine the set of plausible match vectors. Subsequently, a similarity-based algorithm performs the actual matching. The feature points are computed using a multiple-filter image decomposition operator. The algorithm has been tested on synthetic as well as real video images. The novelty of the approach is that it handles multiple motions and performs motion segmentation.     

Predicting the fracture character of weak layers from snowpack penetrometer signals

Digital penetrometers provide reliable assessments of snow penetration resistance with depth. However, extracting useful information from the signals relating to snow stability has proved to be challenging. In this study, penetrometer profiles were collected in close proximity to compression tests. A scheme for predicting the fracture character of weak layers in the compression tests from the penetrometer signals is presented. When a two-group classification between sudden (Q1) (an indicator of instability) and other fracture character groups was performed, potential failure layers were correctly classified 80% of the time. The variables offering the best discrimination between sudden and other categories were weak layer thickness, average force gradient above the weak layer, and both the average and the maximum force gradient below the weak layer. The effect of introducing randomly selected layers into the prediction scheme was also investigated. When such layers were introduced, the classification rate dropped to 67%, indicating that more effective fracture character prediction occurred when weak layers were manually pre-identified. This suggests that this scheme should be used in conjunction with a weak layer detection model rather than as a stand alone analytical technique for the purpose of critical weak layer identification. The classification rate dropped further to 55% when a more detailed, four-group classification scheme was used.     

Predicting the fracture character of weak layers from snowpack penetrometer signals

Digital penetrometers provide reliable assessments of snow penetration resistance with depth. However, extracting useful information from the signals relating to snow stability has proved to be challenging. In this study, penetrometer profiles were collected in close proximity to compression tests. A scheme for predicting the fracture character of weak layers in the compression tests from the penetrometer signals is presented. When a two-group classification between sudden (Q1) (an indicator of instability) and other fracture character groups was performed, potential failure layers were correctly classified 80% of the time. The variables offering the best discrimination between sudden and other categories were weak layer thickness, average force gradient above the weak layer, and both the average and the maximum force gradient below the weak layer. The effect of introducing randomly selected layers into the prediction scheme was also investigated. When such layers were introduced, the classification rate dropped to 67%, indicating that more effective fracture character prediction occurred when weak layers were manually pre-identified. This suggests that this scheme should be used in conjunction with a weak layer detection model rather than as a stand alone analytical technique for the purpose of critical weak layer identification. The classification rate dropped further to 55% when a more detailed, four-group classification scheme was used.     

基于L1范数优化路径的视频稳像算法

目的 为解决外包装行业对产品外观进行检测时,采集视频图像存在抖动失真的问题.方法 提出一种基于L1范数优化路径的视频稳像算法,采用SURF算法和FREAK算法对视频序列帧中的特征点进行检测和描述;然后,使用KNN算法和RANSAC算法对相邻帧间的特征点进行匹配和筛选;最后,通过L1范数优化算法对序列帧进行校正和去黑边处理,得到稳像视频.结果 在处理前景无运动和前景有运动的2类视频时,稳像前后视频的平均PSNR值分别提升了5.094 dB和4.273 dB,并且相对于常用的特征匹配算法,文中算法能显著降低相机路径的主动平滑因子.结论 文中算法能够有效地解决视频抖动失真的问题,提高抖动视频的质量,具有一定的鲁棒性.     

不同算法模型对光谱重构精度的影响

目的研究光谱颜色复制中原稿图像的光谱信息,并对目标色的光谱反射率进行重构,探究影响重构光谱精度的因素。方法通过选取Munsell Color Matt(1269色块)和Color Checker Classic(24色块)2种色卡作为光谱反射率数据样本,建立不同的主成分分析线性重构模型,选取不同的基向量个数分别重构光谱,并对其精度进行评价,取Classic色卡模拟多光谱图像中重建光谱反射率的目标色,研究比较光谱重构模型和基向量数目对重构精度的影响。结果实验表明,降维模型1最终恢复的数据在RMSE,GFC和色差上均优于模型2,随着基向量数目的增加,2种降维模型差距在减小,当基向量数目达到13以后,2种模型基本没差异。结论文中提到光谱重建模型1和7个基向量是重构光谱图像的最佳方案。     

柔性关节空间机器人基于神经网络的自适应反演控制

讨论了载体位姿无控情况下,漂浮基柔性关节空间机器人的关节运动控制器设计问题。利用系统动量、动量矩守恒关系及拉格朗日法,建立了空间机器人的动力学模型。为实现系统关节运动控制目标,借助于神经网络函数逼近技术,提出了一种柔性关节空间机器人的自适应反演控制方案。所提控制方案无需预知系统各惯性参数的真实信息,且可避免对载体位置相关量进行实时地测量与反馈,因此较适于实际应用。数值仿真结果表明:上述控制方案可使系统各柔性关节的振动较小,并能够有效地控制空间机器人完成所期望的关节运动。