一种新的彩色图像加密和解密算法

为实现对数字彩色图像信息的有效保护,提出一种基于Lorenz混沌序列的彩色图像加密及抗剪切攻击解密算法。对Lorenz系统输出的三维混沌序列进行改进,使其具有理想的伪随机特性。根据这三维序列依次改变RGB三分量组合图像的像素位置和像素值,从而实现图像加密;在解密时,给出一种基于邻域相邻像素特性的加密图像抗剪切攻击恢复算法。应用评价指标对加解密效果和安全性进行分析。理论分析和实验结果表明,该算法密钥空间大,具有较好的加解密效果和效率,对统计分析具有较好的安全性和较强的抗剪切攻击能力。     

Prediction-based realistic 3D model compression

The benefit of using the geometry image to represent an arbitrary 3D mesh is that the 3D mesh can be re-sampled as a completely regular structure and coded efficiently by common image compression methods. For geometry image-based 3D mesh compression, we need to code the normal-map images while coding geometry images to improve the subjective quality and realistic effects of the reconstructed model. In traditional methods, a geometry image and a normal-map image are coded independently. However a strong correlation exists between these two kinds of images, because both of them are generated from the same 3D mesh and share the same parameterization. In this paper we propose a predictive coding framework, in which the normal-map image is predicted based on the geometric correlation between them. Additionally we utilize the strong geometric correlation among three components of normal-map image to improve the predicting accuracy. The experimental results show the proposed coding framework improves the coding efficiency of normal-map image, meanwhile the realistic effect of a 3D mesh is significantly enhanced.     

自适应分块的医学图像混沌加解密算法

针对现有基于混沌的医学图像加密算法未考虑图像纹理特征的不足,提出了一种自适应分块的医学图像混沌加解密算法。首先利用2D Sine Logistic混沌系统生成两个具有良好混沌特性的安全序列;然后将图像分成固定尺寸的图像块,并计算图像块的最大像素差和方差,根据设定的阈值将图像块划分成纹理平滑块和纹理复杂块;最后利用混沌序列1对平滑块进行密文反馈加密,利用混沌序列2对复杂块进行明文反馈加密,得到加密后的图像。算法有效地考虑了图像块的纹理特性,优化了混沌加密算法,提高了医学图像的加解密效率。实验仿真结果表明,提出的算法具有高的安全性和加解密效率,相比现有方法加解密速度提高1倍左右。算法适用于大数据量的医学图像实时加解密。     

一种基于 Transformer 的三维人体姿态估计方法

三维人体姿态估计是人类行为理解的基础,但是预测出合理的三维人体姿态序列仍然是具有挑 战性的问题。为了解决这个问题,提出一种基于 Transformer 的三维人体姿态估计方法,利用多层长短期记忆 (LSTM)单元和多尺度 Transformer 结构增强人体姿态序列预测的准确性。首先,设计基于时间序列的生成器, 通过 ResNet 预训练神经网络提取图像特征;其次,采用多层 LSTM 单元学习时间连续性的图像序列中人体姿 态之间的关系,输出合理的 SMPL 人体参数模型序列;最后,构建基于多尺度 Transformer 的判别器,利用多 尺度 Transformer 结构对多个分割粒度进行细节特征学习,尤其是 Transformer block 对相对位置进行编码增强 局部特征学习能力。实验结果表明,该方法相对于 VIBE 方法具有更好地预测精度,在 3DPW 数据集上比 VIBE 的平均(每)关节位置误差(MPJPE)低了 7.5%;在 MP-INF-3DHP 数据集上比 VIBE 的 MPJPE 降低了 1.8%。      

基于三维几何视觉重要性的纹理图像选择压缩算法

不同于传统二维图像,映射到三维模型上的纹理图像隐式包含了三维几何视觉信息. 然而,目前已有的纹理图像压缩方法并未考虑此特性. 本文提出了一种与三维模型几何视觉特性相关的纹理图像选择压缩算法. 首先给出一种结合纹理图像的显著性及其纹理走样的视觉重要性图构建方法, 将纹理图像划分为具有不同优先级别区域.之后,利用提出的选择压缩方法对它们进行不同比例压缩. 实验结果表明当选择本压缩算法时,纹理化三维模型能够获取较好的视觉效果.     

彩色数字图像的小波变换和混沌序列加密

根据彩色数字图像的基本特点,运用数字图像加密和解密原理,将离散小波变换和离散混沌序列有机地结合起来,研究了彩色数字图像的小波变换和混沌序列的加密和解密方法;对原始图像进行加密实质是利用混沌序列对其低频小波系数进行加密,对加密图像进行解密实质是利用混沌序列对其低频小波系数进行解密;研究的彩色数字图像加解密方法,为彩色数字图像加密提供了一种有效可行的方法,不仅能够使加密彩色数字图像具有理想的加密效果,而且能够保证加密彩色数字图像足够的安全。     

3D head tracking under partial occlusion

A new algorithm for 3D head tracking under partial occlusion from 2D monocular image sequences is proposed. The extended superquadric (ESQ) is used to generate a geometric 3D face model in order to reduce the shape ambiguity during tracking. Optical flow is then regularized by this model to estimate the 3D rigid motion. To deal with occlusion, a new motion segmentation algorithm using motion residual error analysis is developed. The occluded areas are successfully detected and discarded as noise. Furthermore, accumulation error is heavily reduced by a new post-regularization process based on edge flow. This makes the algorithm more stable over long image sequences. The algorithm is applied to both synthetic occlusion sequence and real image sequences. Comparisons with the ground truth indicate that our method is effective and is not sensitive to occlusion during head tracking.     

Hypercatadioptric line images for 3D orientation and image rectification

In central catadioptric systems 3D lines are projected into conics. In this paper we present a new approach to extract conics in the raw catadioptric image, which correspond to projected straight lines in the scene. Using the internal calibration and two image points we are able to compute analytically these conics which we name hypercatadioptric line images. We obtain the error propagation from the image points to the 3D line projection in function of the calibration parameters. We also perform an exhaustive analysis on the elements that can affect the conic extraction accuracy. Besides that, we exploit the presence of parallel lines in man-made environments to compute the dominant vanishing points (VPs) in the omnidirectional image. In order to obtain the intersection of two of these conics we analyze the self-polar triangle common to this pair. With the information contained in the vanishing points we are able to obtain the 3D orientation of the catadioptric system. This method can be used either in a vertical stabilization system required by autonomous navigation or to rectify images required in applications where the vertical orientation of the catadioptric system is assumed. We use synthetic and real images to test the proposed method. We evaluate the 3D orientation accuracy with a ground truth given by a goniometer and with an inertial measurement unit (IMU). We also test our approach performing vertical and full rectifications in sequences of real images.     

Baker 映射的三维扩展及其在多媒体加密中的应用

对Baker映射进行三维扩展，提出一种基于三维混沌映射的混沌加密方案．与二维映射相比，扩展后的三维Baker映射具有更大的密钥空间、更快的混迭速度和更广的应用范围．这种三维Baker映射与扩散函数相结合，增加了密码强度，起到良好的加密作用．实验结果表明，与传统基于数论的DES加密算法相比，该算法具有更快的速度，更适合于多媒体数据的加密．     

Extraction of 3D information from sonar image sequences

This paper describes a set of methods that make it possible to estimate the position of a feature inside a three-dimensional (3D) space by starting from a sequence of two-dimensional (2D) acoustic images of the seafloor acquired with a sonar system. Typical sonar imaging systems are able to generate just 2D images, and the acquisition of 3D information involves sharp increases in complexity and costs. The front-scan sonar proposed in this paper is a new equipment devoted to acquiring a 2D image of the seafloor to sail over, and allows one to collect a sequence of images showing a specific feature during the approach of the ship. This fact seems to make it possible to recover the 3D position of a feature by comparing the feature positions along the sequence of images acquired from different (known) ship positions. This opportunity is investigated in the paper, where it is shown that encouraging results have been obtained by a processing chain composed of some blocks devoted to low-level processing, feature extraction and analysis, a Kalman filter for robust feature tracking, and some ad hoc equations for depth estimation and averaging. A statistical error analysis demonstrated the great potential of the proposed system also if some inaccuracies affect the sonar measures and the knowledge of the ship position. This was also confirmed by several tests performed on both simulated and real sequences, obtaining satisfactory results on both the feature tracking and, above all, the estimation of the 3D position.     

结合三维几何形状信息和二维纹理的3D目标匹配

为了实现场景中三维目标与模型之间的匹配,提出了一种结合三维几何形状信息和二维纹理的三维目标匹配方法。首先提取场景中深度图像的尺度不变特征变换(SIFT)特征,用SIFT算法与三维模型重建时所用到的一系列2.5维深度图像进行一一匹配,找到与场景中目标姿态最为相似的深度图像,提取此深度图像的三维几何形状特征与模型进行匹配,实现模型的初始化,即将模型重置到与场景目标相接近的姿态。最后用融合二维纹理信息的迭代就近点（ICP）算法实现场景中目标与模型之间的匹配,从而得到场景中三维目标的准确姿态。实验结果验证了方法的可行性与精确性。     

基于序列图像的鲁棒三维重建方法

提出了基于序列图像的鲁棒三维重建方法。首先利用两幅图像的最优参数估计,然后添加新图像并采用稀疏调整,减少图像坐标测量值的最小几何误差。通过对三维结构和摄像机参数进行全局优化处理,以提高重建的鲁棒性。实验结果表明,该方法提高了重建的精度和鲁棒性,并真实地再现了物体的三维模型。     

基于D^2PCM的数字减影图象序列无损压缩算法

充分利用数字减影（ＤＳＡ）图象序列在时间域上的减影图象之间仍然存在一定的相似性,提出了一种基于二阶差分ＰＣＭ（Ｄ＾２ＰＣＭ）的编码方式。方法在空间坐标与时间坐标上构成了一个二阶差分,能够有效地减少图象在空间以及时间域上的冗余度,从而实现对ＤＳＡ序列的无损压缩,减少了存储空间与传输时间。实际应用证明该处法是稳定和实用的。     

Efficient 3D medical image segmentation algorithm over a secured multimedia network

Image segmentation has proved its importance and plays an important role in various domains such as health systems and satellite-oriented military applications. In this context, accuracy, image quality, and execution time deem to be the major issues to always consider. Although many techniques have been applied, and their experimental results have shown appealing achievements for 2D images in real-time environments, however, there is a lack of works about 3D image segmentation despite its importance in improving segmentation accuracy. Specifically, HMM was used in this domain. However, it suffers from the time complexity, which was updated using different accelerators. As it is important to have efficient 3D image segmentation, we propose in this paper a novel system for partitioning the 3D segmentation process across several distributed machines. The concepts behind distributed multimedia network segmentation were employed to accelerate the segmentation computational time of training Hidden Markov Model (HMMs). Furthermore, a secure transmission has been considered in this distributed environment and various bidirectional multimedia security algorithms have been applied. The contribution of this work lies in providing an efficient and secure algorithm for 3D image segmentation. Through a number of extensive experiments, it was proved that our proposed system is of comparable efficiency to the state of art methods in terms of segmentation accuracy, security and execution time.

     

基于三维离散余弦变换的静止彩色图象压缩

为了既能获得较高的压缩比 ,又能保证较好的图象质量 ,提出了一种基于三维离散余弦变换 (3D DCT)的静止彩色图象编码方法 .在此算法中 ,首先将原始图象分割成互不覆盖的 8× 8子块 ;然后根据局部能量的大小将各子块分为 4类 ,再把属于同一类的子块组合到一起 ,形成三维立方体并对三维立方体进行三维离散余弦变换 ,从而提高压缩效率 .计算机模拟结果表明 ,此算法在压缩比高于 4 0时 ,其平均峰值信噪比约为 2 9d B,解压后的图象质量有较高的保真度 ,在同等情况下 ,其比 JPEG标准提高约 5 d B     

三维重定向图像主观和客观质量评价方法

三维（S3D）图像重定向技术的作用是调整S3D图像的宽高比。为准确和客观地衡量三维重定向图像的视觉质量，建立了一个S3D重定向图像质量评价数据库。首先，使用八种具有代表性的三维重定向算法对45幅原始图像按两种重定向尺度进行分辨率调整，共生成720幅三维重定向图像；然后，每幅重定向图像通过主观测试，得到相应的主观打分值；最后，对主观分数进行处理，得到平均主观意见分（MOS）值。在此基础上，提出一种三维重定向图像客观质量评价方法，即通过提取S3D重定向图像的深度感特征、视觉舒适度特征和左右视点的图像质量特征，使用支持向量回归预测得到S3D重定向图像的视觉质量。在提出的数据库上进行测试可以得知，所提方法的Pearson线性相关系数高于0.82，Spearman等级系数高于0.81，表明其能有效预测S3D重定向图像的视觉质量。     

Optimizing image focus for 3D shape recovery through genetic algorithm

Three-dimensional information of objects is advantageous and widely used in multimedia systems and applications. Shape form focus (SFF) is a passive optical technique that reconstructs 3D shape of an object using a sequence of images with varying focus settings. In this paper, we propose an optimization of the focus measure. First, Wiener filter is applied for noise reduction from the image sequence. At the second stage, genetic algorithm (GA) is applied for focus measure optimization. GA finds the maximum focus measurement under a fitness criterion. Finally, 3D shape of the object is determined by maximizing focus measure along the optical direction. The proposed method is tested with image sequences of simulated and real objects. The performance of the proposed technique is analyzed through statistical criteria such as root mean square error (RMSE) and correlation. Comparative analysis shows the effectiveness of the proposed method.     

Video Panorama for 2D to 3D Conversion

Accurate depth estimation is a challenging, yet essential step in the conversion of a 2D image sequence to a 3D stereo sequence. We present a novel approach to construct a temporally coherent depth map for each image in a sequence. The quality of the estimated depth is high enough for the purpose of2D to 3D stereo conversion. Our approach first combines the video sequence into a panoramic image. A user can scribble on this single panoramic image to specify depth information. The depth is then propagated to the remainder of the panoramic image. This depth map is then remapped to the original sequence and used as the initial guess for each individual depth map in the sequence. Our approach greatly simplifies the required user interaction during the assignment of the depth and allows for relatively free camera movement during the generation of a panoramic image. We demonstrate the effectiveness of our method by showing stereo converted sequences with various camera motions.     

云环境下基于自然对数序列的似混沌序列图像加密方案

针对云计算中图像数据的安全问题,提出一种基于自然对数序列的似混沌序列图像加密方案.提出自然对数序列的概念,验证其似混沌特性;使用二维猫映射对图像进行像素置乱,并在此基础上利用SM3杂凑算法和自然对数序列进行像素值扰乱,得到加密图像;在离散对数的假设下,证明方案具有IND-CCA安全.仿真实验表明,该方案在安全性上与混沌...     

Multi-stage 3D reconstruction under circular motion

In this paper, we propose a new method for 3D reconstruction from an image sequence captured by a camera with constant intrinsic parameters undergoing circular motion. We introduce a method, called circular projective reconstruction, for enforcing the circular constraint in a factorization-based projective reconstruction. To deal with the missing data problem, our method uses a multi-stage approach to reconstructing the objects and cameras, which first computes a circular projective reconstruction of a sub-sequence and then extends the reconstruction to the complete sequence. Camera matrix, rotation angles, and 3D structure are computed iteratively in a way that the 2D reprojection error is minimized. The algorithm is evaluated using real image sequences.