一种针对JPEG2000图像量化指标调制的信息隐写算法

针对JPEG2000基本压缩编码系统,提出了一种基于量化指标调制的信息隐写算法.该算法可以有效保持离散小波系数的直方图特性,抵御图像隐写直方图攻击.实验证明了算法的可行性和有效性.     

A chaos based image steganographic system

This paper presents a steganographic technique using the theory of Brownian motion. In the beginning, the Brownian Based Scrambling procedure introduces traces of non linearity in the carrier medium so as to introduce one layer of security. A lighter pixel (in terms of its intensity) is presumed to experience a faster movement than the heavier ones. The above stated concept is based on the randomized scrambling strategy which is usually chaotic in nature. It actually reflects the strategy of chaos generation in the image medium. The ‘key’ is generated from the Brownian theories and is being utilized in the Power Modulus Scrambling strategy to increase the security level. In addition, the embedding technique, i.e. Pixel Insertion Methodology is also dependent on certain correlation factors of Brownian motion. The performance has been worked out to establish the efficacy of the algorithm. This whole procedure supports high embedding capacity. The experimental results show that the proposed technique performs better or at least at par with respect to many of the existing steganographic techniques. The results have been tested against various benchmarks, as illustrated in the section of experimental results. This approach can be used to provide an additional layer of protection to any system that communicates important data/information through any kind of globally accessed medium. Moreover, this approach serves its purpose of providing seamless security between sender and receiver without producing any distortion in the images. This explicit concept may be used in cyber-security for prevention of unauthorized access of information.     

Secure and imperceptible digital image steganographic algorithm based on diamond encoding in DWT domain

This paper presents a new efficient embedding algorithm in the wavelet domain of digital images based on the diamond encoding (DE) scheme. Current discrete wavelet transform (DWT) steganography adds an unacceptable distortion to the images and is considered as an ineffective in terms of security. Applying the DE scheme to the current DWT steganographic methods solves the problems of these methods, and reduces the distortion added to the images, and thus improves the embedding efficiency. The proposed algorithm first converts the secret image into a sequence of base-5 digits. After that, the cover image is transformed into the DWT domain and segmented into 2?×?1 coefficient pairs. The DE scheme is used then to change at most one coefficient of each coefficient pair to embed the base-5 digits. Experimental results depict that the proposed algorithm is more efficient in embedding compared to other methods in terms of embedding payload and image quality. Moreover, the proposed algorithm is attacked by well-known steganalysis software. Results are showing that the proposed algorithm is secure against the powerful universal steganalyzer “ensemble classifier” and the histogram attack. The results also reveal that the proposed algorithm is robust against different image processing attacks such as compression, added noise, and cropping attacks.     

New spatial based MRI image de-noising algorithm

Nowadays, fast scan techniques are used to reduce scanning times. These techniques raise scanning noise level in MRI systems. Instead of progress made in image de-noising, still, it is challenging. A novel edge-preserving neighbourhood filter for image enhancement is proposed. The main focus of this paper is to propose an adaptive filtering function to account for the image content while try to preserve edge of image. Proposed algorithm uses the edges of image to do edge-preserving neighbourhood filtering. Contribution of a sample, in neighbourhood of a pixel, in filtering, depends on the space between the pixel and the sample. In fact, the sample which there is edge between it and the pixel don’t contribute in the grey level estimation. Promising experimental results on simulated and real brain images and comparison with state-of-art de-noising algorithm demonstrate the potential of proposed algorithm.     

Image feature based high capacity steganographic algorithm

Multimedia Tools and Applications - Steganography is the growing field of research, where hiding techniques are used to secure the communicative elements (e.g., images). In this paper, the message...     

改进SURF算法的图像拼接算法研究

针对目前图像拼接算法存在对于图像配准过程中对应特征点对难以准确匹配的问题,提出了一个通过改进的SURF算法提取图像特征点,然后对得到的特征点进行描述,利用快速RANSAC算法配准图像,最后采用像素加权的方法进行图像融合。实验结果表明,提出的改进SURF方法有效地提高了特征点提取的准确性,去除了错误的匹配点对,将整个拼接过程的效率从之前的13.03对/秒提升到15.20对/秒。     

一种基于位平面的图像加密算法

在不移动像素情况下达到对图像进行加密目的,提出一种基于图像位平面的加密算法。按像素比特位对图像进行分解,得到图像位平面,再利用两个Logistic混沌系统构造二值矩阵与中间密钥矩阵对位平面执行置乱加密,最后将各个位平面叠加得到密文图像。     

An adaptive image steganographic scheme based on Noise Visibility Function and an optimal chaotic based encryption method

Steganography is the science of hiding secret message in an appropriate digital multimedia in such a way that the existence of the embedded message should be invisible to anyone apart from the sender or the intended recipient. This paper presents an irreversible scheme for hiding a secret image in the cover image that is able to improve both the visual quality and the security of the stego-image while still providing a large embedding capacity. This is achieved by a hybrid steganography scheme incorporates Noise Visibility Function (NVF) and an optimal chaotic based encryption scheme. In the embedding process, first to reduce the image distortion and to increase the embedding capacity, the payload of each region of the cover image is determined dynamically according to NVF. NVF analyzes the local image properties to identify the complex areas where more secret bits should be embedded. This ensures to maintain a high visual quality of the stego-image as well as a large embedding capacity. Second, the security of the secret image is brought about by an optimal chaotic based encryption scheme to transform the secret image into an encrypted image. Third, the optimal chaotic based encryption scheme is achieved by using a hybrid optimization of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) which is allowing us to find an optimal secret key. The optimal secret key is able to encrypt the secret image so as the rate of changes after embedding process be decreased which results in increasing the quality of the stego-image. In the extracting process, the secret image can be extracted from the stego-image losslessly without referring to the original cover image. The experimental results confirm that the proposed scheme not only has the ability to achieve a good trade-off between the payload and the stego-image quality, but also can resist against the statistics and image processing attacks.     

基于Harris角点的图像匹配算法

提出了新的基于特征点的高速图像匹配算法。该算法把角点特征和灰度值特征结合起来,定义了一种基于Harris角点的灰度值特征,并充分利用角点灰度值以及角点周边灰度值和位置信息,然后依据这些信息进行匹配。实验结果表明,该算法不仅速度快,而且对灰度值分布不均图像和含噪图像的匹配同样适用。     

一种基于曲波变换的图像去块算法

图像块效应是由于进行图像压缩编码时采用离散余弦变换(discrete cosine transform,DCT)并对其系数进行量化处理而引起的,该过程丢失了一些频率成分,并引起了子块边界不连续的跳变.针对这一问题,提出了一种基于曲波变换的图像去块算法,该算法首先对退化图像进行曲波变换,再对所获取的各层曲波系数进行处理以备复原图像.通过寻找各层中与原始图像块效应相对应的系数,对不同的层采用不同的方法,并计算图像重建时所要使用的新系数矩阵.实验表明,该算法比传统在客观和主观评估中都被普遍运用的空间域和小波去块方法,得到了更佳的图像复原效果,且保留了更多的细节.     

基于内容的词典式图像库生成Hash编码的算法

主要研究了基于内容的词典式图像库产生图像Hash编码的算法.建立一个词典结构的图像库,提取图像库中所有的块特征向量,并进行聚类分析,对聚类后的每一部分进行二进制编码,从而生成二进制索引(词典)库,将待查图像引入图像库进行匹配,生成一串二进制代码的路径,即Hash编码.实验证明,基于词典结构生成的Hash编码能够很好地反映视觉上的变化,但是,对视觉上相似的图像细微的变化反应并不剧烈,能够较好地表达图像的整体情况.     

基于颜色空间采样的抠图算法

由于自然图像抠图具有高度的不确定性,目前的抠图方法中对于前背景颜色较为复杂的图片处理效果并不理想。本文首先通过采集大量的样本对来估计初始的掩膜值,但是通过采样得到的样本对并不能很好地估计掩膜值,为此定义未知像素与前背景样本点的空间距离和颜色距离函数来对其进行优化。通过最小化该代价函数来求得最优的样本对,使得最终得到的结果实现了准确性和鲁棒性的良好均衡。自然图像抠图实验结果表明,与其他几种抠图算法相比,本算法在视觉效果上和均差误差上都优于其他算法。     

An adaptive spatial clustering algorithm based on delaunay triangulation

In this paper, an adaptive spatial clustering algorithm based on Delaunay triangulation (ASCDT for short) is proposed. The ASCDT algorithm employs both statistical features of the edges of Delaunay triangulation and a novel spatial proximity definition based upon Delaunay triangulation to detect spatial clusters. Normally, this algorithm can automatically discover clusters of complicated shapes, and non-homogeneous densities in a spatial database, without the need to set parameters or prior knowledge. The user can also modify the parameter to fit with special applications. In addition, the algorithm is robust to noise. Experiments on both simulated and real-world spatial databases (i.e. an earthquake dataset in China) are utilized to demonstrate the effectiveness and advantages of the ASCDT algorithm.     

An adaptive steganographic algorithm for 3D polygonal meshes

This paper presents a new adaptive digital steganographic technique for three-dimensional (3D) polygonal meshes. It is based on an adaptive substitutive blind procedure in the spatial domain. We use angle features to remove all restrictions of fixed embedding size in each vertex to provide larger embedding capacity and to minimize the distortion by minimum distortion distance estimation. This method exploits the correlation between neighboring polygons with respect to the human visual system to estimate the degree of smoothness or roughness properties. If the vertex is located on a rough surface, then it may tolerate larger position changes by embedding more messages than those on smooth surfaces. Our method provides an easy way to produce a more imperceptible result. In addition, a simple contagious diffusion technique is devoted to improving performance for polygonal meshes traversal. Experimental results show that the proposed technique is adaptive, simple, efficient, general, and secure. This technique has high capacity and low distortion, and it is robust against affine transformations. Our technique provides an adaptive method and has proven feasible in steganography.     

基于NSCT的自适应多聚焦图像融合算法

针对非降采样轮廓波变换（NSCT）具有多尺度、方向性和平移不变性等特点,为改善融合后图像模糊现象,提出了一种基于区域特性的非降采样轮廓波变换的多聚焦图像融合算法。该算法结合NSCT的特点,将图像进行NSCT,变换为不同方向的各子带信息;然后基于局部均值和局部方差选择低频子带系数,并在带通方向子带中引用局部方向对比度作为测量算子来选择带通方向子带系数;最后,通过反变换得到融合图像。实验结果表明,本算法融合效果优于传统的加权平均、小波变换及NSCT算法。     

An image encryption algorithm based on irregular wave representation

For a gray image, every row (column) can be seen as an irregular wave. Activated by the architecture of permutation-diffusion based image encryption scheme, a chaotic image encryption algorithm is proposed to change the representation of irregular waves in the plain-image. To reduce the high correlation, permutation for both rows and columns is taken in the first stage. Due to the transposition of pixels in row/column, wave shapes will be changed according to the pseudo-random sequences generated from chaotic map. Specifically, pixels in each wave (row or column) are divided into two groups by energy (a bigger one and a smaller one). Then different groups are employed to manipulate the production of chaotic sequence. As a result, the chosen-plaintext and known-plaintext attacks will be difficult due to the plain-image dependent keystream. In the second stage, wave-by-wave diffusion in column is carried out such that any tiny change in the plain-image spreads out uniformly to the whole cipher-image. The keystream used in diffusion is designed again dependent on the permuted image obtained from the first stage. In this way, the security of the proposed algorithm can be further strengthened compared with some existing algorithms. Related security analyses also show that our method can satisfy common requirements of secure communication for daily images.

     

基于图像一致性计算的目标识别算法

视觉计算模型集合了人类视觉系统(HVS)的复杂特征,并模拟了视觉输入的分层感知表达。自底向上机制是现代模型中最常见的特征,是指无意识的注意,所提出的一致计算方法模拟自底向上视觉注意,并通过一致区域的计算来达到目标识别的目的。所提模型主要基于对HVS行为的目前的理解,使用对比敏感度函数、感知分解、视觉掩蔽形成一个神经性视觉空间,并在此基础上使用center-surround交互、感知编组和显著图的建立来得到最终的显著图。所提模型的性能通过使用自然图像来进行评估,并将其结果与参照的经典的自底向上模型进行对比,结果表明该模型实效性高。     

一种基于边缘提取的交互式图像分割算法

提出了基于边缘提取的交互式图像分割算法,该算法将图像映射为无向图,使用拉普拉斯零交叉点、边缘强度和动态轨迹长度构造能量模型,并为无向图中的边赋予能量代价.根据能量代价,引入角点信息,在交互得到的控制点间搜索最优路径,迭代此过程,实现分割.实验结果表明,该算法具有较高的精度和效率,能较好地克服噪声影响,适用于灰度及彩色图像.     

An adaptive image watermarking algorithm based on perceptual model

An adaptive image watermarking algorithm based on Watson＇s perceptual model is proposed in this paper. The proposed watermarking algorithm fully considers image regional characteristic. First, the cover image is divided into different smooth regions according to its gray value. Then watermark adjustment factors of those different regions are calculated respectively based on Watson＇s perceptual model. The watermark is embedded by the adjustment factors at last. Experiments show that the proposed algorithm has excellent imperceptibility and has little influence upon the eigenvalue of the cover image.