基于DWT和RSA的变强度可见数字水印算法

提出了一种基于离散小波变换（DWT）和RSA加密的变强度可见数字水印算法。该算法在小波参数选择中,使水印图像的嵌入强度依主图像特征而变化,计算嵌入因子值时考虑并利用了拉伸系数的值,加快了计算速度;同时用RSA对小波系数进行加密,使合法用户能控制水印强度。实验表明该算法是有效的,并具有较好的鲁棒性。     

基于Z型结构的低存储二维DWT硬件结构

为了适应当前高清多灰度值显示和片上低存储需求,提出了一种高效低存储DWT的VLSI结构.采用了行列并行运行结构,并且行列运算均使用流水线机制,提高了硬件的利用率.并且使用各16位来存储小波系数的整数(包括符号位)部分和小数部分,使得这种结构能支持1023级(10位)灰度值和较高精度的需求.经过RTL级仿真和SMIC的0.18um工艺综合,结果表明,这种设计可在100MHZ时钟下,采用9/7滤波器经过5级分解,每秒可处理约65帧1024*1024* 10位的图像.     

Ground roll attenuation using real and complex DWT based methods

This paper deals with ground roll attenuation using double density and dual-tree complex discrete wavelet transforms. These transforms use a new denoising method instead of well-known hard and soft thresholdings and Wavelet Domain Ground roll Analysis (WDGA) applied in finding and attenuating the ground roll energy in the wavelet domain. The dual-tree complex wavelet transform (DTCWT), and double density discrete wavelet transform (DDDWT) have two wavelets and one scaling function and are nearly shift-invariant. Also they have redundancy factors of 2, and their wavelets are smoother than other orthogonal wavelets. Based on this fact, they can be considered as replacement methods for such aims. Recognizing the performance of each method is required to show which method is more suitable and efficient. In the present study, distinct wavelets and scaling function of each method have been applied to the data, and also the data are denoised by Wavelet Domain Ground roll Analysis technique. Additionally, for the inverse transform, the coefficients of the noise are removed. And finally for concluding, the results of all methods are compared with the f-k method and band-pass filtering, and critically sampled Discrete Wavelet Transforms. Final results showed that the DTCWT is reliable in comparison with other methods for ground roll attenuation.     

Cloud top temperature based precipitation intensity estimation using INSAT-1D data

Precipitation intensity associated with each cloud type is an important parameter as it suggests the respective contribution of different categories of clouds to rainfall. The present paper aims at demonstrating a technique of establishing a relationship between the various sub-zero Celsius temperature ranges of clouds with cold top temperatures and their precipitation intensities. Indian Satellite (INSAT-1D) infrared and visible band data were utilized for this purpose. A regression analysis was performed and various cases statistically analysed. The results indicated that nearly all clouds with their tops colder than 275K contribute to precipitation. On combining the results of precipitation intensity with cloud type, it has been found that during the monsoon season the contribution of different clouds to rainfall over an area decreases in the study area: the maximum being from cumulonimbus (1.75-1.49 mm h^-1), followed by nimbostratus (0.97- 0.86 mm h^-1) and altocumulus/altostratus (0.97-0.86 mm h^-1). The contributions from other cloud types, such as status, cumulus or stratocumulus, is insignificant for this study region during the period under observation. However, the precipitation estimates for other clouds like cirrus, cirrostratus and cirrocumulus are unpredictable from the scheme presented here due to several inherent limitations. The image processing technique of level slicing was also utilized to yield fast and reliable images depicting the regions of varying rainfall. Although the analysis has some limitations, it clearly illustrates the relationship between the cloud top temperature and precipitation intensities which may be utilized in actual practice.     

Sparse recovery based reversible data hiding method using the human visual system

In this paper, a novel sparse recovery based reversible data hiding (RDH) method using the human visual system (HVS) is presented. To improve the low accuracy of existing predictors, a sparse recovery based predictor is proposed. In the processes of sparse recovery, the most relevant neighbors can be adaptively chosen by using sparse representation to predict the current pixel accurately, and thus the concentrated prediction error histogram (PEH) is built to obtain good embedding performance. Moreover, to overcome the conflict between the embedding order of the traditional RDH method and the evaluation of HVS, a new embedding strategy based on just noticeable difference (JND) is designed. In this strategy, pixels are classified into sensitive and in-sensitive clusters according to JND values, and two corresponding PEHs are built. Accordingly, different inner regions of two PEHs are adjusted to meet the required embedding capacity, and the prediction error expansion (PEE) technique is utilized to embed data. Experimental results prove that the proposed method outperforms the state-of-the-art RDH methods, including JND related methods.     

基于Krawtchouk不变矩和SVD-LWT的双重水印研究

为提高数字图像水印的鲁棒性和透明性,提出了一种基于Krawtchouk不变矩、奇异值分解(SVD)和提升小波变换(LWT)的彩色图像双水印算法。该算法首先从载体RGB图像中提取绿色分量进行两级提升小波变换,利用Krawtchouk不变矩对平移、旋转和缩放的不变性以及Krawtchouk矩良好的局部特性和重构性,计算其低频分量的Krawtchouk低阶矩不变量构造水印系统;然后对其变换后的中频分量奇异值进行分解,嵌入混沌置乱后的水印图像的奇异值作为另一水印系统。仿真实验结果表明,该算法不仅有良好的不可见性,而且对常见攻击和几何攻击都具有很好的鲁棒性,并具有一定的应用价值。     

Robust audio watermarking algorithm based on DWT using Fibonacci numbers

Multimedia Tools and Applications - This paper presents a blind and robust audio watermarking algorithm developed based on Fibonacci numbers properties and the discrete wavelet transform (DWT)...     

一种新的LWT和SVD的灰度图像水印

先对载体图像进行分块,然后对每块二级LWT后的中高频带再次LWT,并对选取的各频带进行SVD,选取其相应的奇异值组成新的变换矩阵,对新的变换矩阵按规则进行分块,并再次SVD。通过两次分块,两次LWT和四重使用SVD构造矩阵的方法,有效地将抽取的奇异值重新分配和组合,最后将Arnold置乱后的灰度水印信息加载到组合后的矩阵中。仿真实验表明,新的图像水印方法提高了嵌入的信息量,具有很好的透明性,而且对常见的图像攻击具有很强的鲁棒性。     

Chaos based cryptosystem for still visual data

Recent years have witnessed a strong relationship between chaos and cryptography. Owing to this relationship, development in one field directly impacts the other field. High computational resources are consumed in re-designing of the complete cryptosystem due to a newly developed chaotic map. Also, the tools developed to discern chaos leads to easy cryptanalysis of chaotic cryptosystems. To save resources and overcome easy cryptanalysis, this paper proposes a spatial domain based chaotic cryptosystem that employs different chaotic maps during permutation-substitution process. Multiple iterations have been performed to achieve resistance against various cryptanalytic and error function attacks, that are specifically designed for chaos based cryptosystems. The proposed technique has been generalized and verified for different chaotic maps. A significant benefit of the proposed cryptosystem is its support for chaotic system free property, which allows replacement of an existing chaotic map with a different map at a later stage. Thorough performance, security and comparative analysis ascertains efficacy of the proposed technique.     

Fragile high capacity data hiding in digital images using integer-to-integer DWT and lattice vector quantization

Multimedia Tools and Applications - Data hiding in digital multimedia has been extensively used for sensitive data transmission and data authentication. An important property of data hiding which...     

一个基于OLAM的可视化数据挖掘系统原型

基于OLAM的可视化数据挖掘系统将可视化工具和数据挖掘工具融为一体,它与一般的数据挖掘系统不同,充分利用了OLAM模型沿着多个维进行挖掘,并以智能的方式与用户进行交互,可以在多维数据库的不同部位和不同的抽象级别交互地执行挖掘,以图形的方式输出结果。     

Tree species differentiation using intensity data derived from leaf-on and leaf-off airborne laser scanner data

Tree species identification is important for a variety of natural resource management and monitoring activities including riparian buffer characterization, wildfire risk assessment, biodiversity monitoring, and wildlife habitat assessment. Intensity data recorded for each laser point in a LIDAR system is related to the spectral reflectance of the target material and thus may be useful for differentiating materials and ultimately tree species. The aim of this study is to test if LIDAR intensity data can be used to differentiate tree species. Leaf-off and leaf-on LIDAR data were obtained in the Washington Park Arboretum, Seattle, Washington, USA. Field work was conducted to measure tree locations, tree species and heights, crown base heights, and crown diameters of individual trees for eight broadleaved species and seven coniferous species. LIDAR points from individual trees were identified using the field-measured tree location. Points from adjacent trees within a crown were excluded using a procedure to separate crown overlap. Mean intensity values of laser returns within individual tree crowns were compared between species. We found that the intensity values for different species were related not only to reflective properties of the vegetation, but also to a presence or absence of foliage and the arrangement of foliage and branches within individual tree crowns. The classification results for broadleaved and coniferous species using linear discriminant function with a cross validation suggests that the classification rate was higher using leaf-off data (83.4%) than using leaf-on data (73.1%), with highest (90.6%) when combining these two LIDAR data sets. The result also indicates that different ranges of intensity values between two LIDAR datasets didn't affect the result of discriminant functions. Overall results indicate that some species and species groups can be differentiated using LIDAR intensity data and implies the potential of combining two LIDAR datasets for one study.     

基于混沌系统与提升小波的彩色图像盲水印算法*

研究了混沌序列、提升小波在彩色图像盲水印中的应用,给出一种新的基于混沌系统和提升小波的彩色图像盲水印算法。算法同时采用两种不同的混沌序列,提高了算法的安全性;根据人类视觉系统特性使中低频使用不同的算法自适应地嵌入水印,使算法有了很好的隐藏效果;使用提升小波变换提高了算法的效率;对受严重攻击后提取出的水印进行优化处理,使算法有了很好的鲁棒性。实验证明,该算法具有较高的效率、较好的隐藏效果、很好的安全性和鲁棒性。     

基于视觉同时定位与地图构建数据关联优化算法

数据关联的复杂程度随着地图规模的不断扩大而增加是导致机器人同时定位与地图创建（SLAM）实时性差的一个主要原因。在SLAM系统中,主要应用尺度不变特征变换（SIFT）算法提取自然路标。提出两种方法来改进数据关联的实时性：1）提取感兴趣区域;2）引入当前路标的物理位置信息作预判断。实验结果表明,所提的改进方法是可靠的,改善算法复杂度的效果是显而易见的。     

A fuzzy based ROI selection for encryption and watermarking in medical image using DWT and SVD

Nowadays secure medical image watermarking had become a stringent task in telemedicine. This paper presents a novel medical image watermarking method by fuzzy based Region of Interest (ROI) selection and wavelet transformation approach to embed encrypted watermark. First, the source image will undergo fuzzification to determine the critical points through central and final intensity along the radial line for selecting region of interest (ROI). Second, watermark image is altered to time-frequency domain through wavelet decomposition where the sub-bands are swapped based on the magnitude value obtained through logistic mapping. In the each sub-band all the pixels get swapped, results in fully encrypted image which guarantees the watermark to a secure, reliable and an unbreakable form. In order to provide more robustness to watermark image, singular values are obtained for encrypted watermark image and key component is calculated for avoiding false positive error. Singular values of the source and watermark image are modified through key component. Experimental results reveal that the proposed algorithm attains high robustness and improved security to the watermarked image against various kinds of attacks.

     

基于小波—奇异值分解的数字水印新算法*

为了有效地保护数字作品的版权,提出了一种以离散小波多级分解与奇异值分解相结合的数字水印新算法。该算法充分利用小波与奇异值的固有性质,对原始图像进行多级小波分解,并对部分子带作奇异值分解。将水印置乱来保证一定的安全性,再对其进行分块离散余弦变换,然后将它嵌入到中间奇异值及其周围的部分矩阵块中。实验表明,该方法不仅有较好的透明性,而且能抗大多数处理攻击,有较好的鲁棒性。     

基于观测数据偏差修正的DBSCAN改进算法

在经典DBSCAN聚类算法中距离度量直接影响到聚类的结果,为了使观测数据的偏差不影响到距离度量,在研究观测数据预处理过程及经典DBSCAN聚类算法基础上,提出了一种DBSCAN距离度量的改进算法,指出了观测数据偏差修正的基本思想及改进算法的处理流程.仿真结果表明,改进算法能很好地修正观测数据的偏差,最终得到较好的聚类结果.     

Classifying individual tree genera using stepwise cluster analysis based on height and intensity metrics derived from airborne laser scanner data

This paper evaluates the ability of small footprint, multiple return and pulsed airborne scanner data to classify tree genera hierarchically using stepwise cluster analysis. Leaf-on and leaf-off airborne scanner datasets obtained in the Washington Park Arboretum, Seattle, Washington, USA were used for tree genera classification. Parameters derived from structure and intensity data from the leaf-on and leaf-off laser scanning datasets were compared to ground truth data. Relative height percentiles and simple crown shapes using the ratio of a crown length to width were computed for the structure variables. Selected structure variables from the leaf-on dataset had higher classification rate (74.9%) than those from the leaf-off dataset (50.2%) for distinguishing deciduous from coniferous genera using linear discriminant functions.Unsupervised stepwise cluster analysis was conducted to find groupings of similar genera at consecutive steps using k-medoid algorithm. The three stepwise cluster analyses using different seasonal laser scanning datasets resulted in different outcomes, which imply that genera might be grouped differently depending on the timing of the data collection. When combining leaf-on and leaf-off LIDAR datasets, the cluster analysis could separate the deciduous genera from evergreen coniferous genera and could make further separations between evergreen coniferous genera. When using the leaf-on LIDAR dataset only, the cluster analysis did not separate deciduous from evergreen genera. The overall results indicate the importance of the timing of laser scanner data acquisition for tree genera separation and suggest that the potential of combining two LIDAR datasets for improved classification.     

基于串行数据存储的腐蚀检测仪

文章介绍的是一套腐蚀检测仪系统,系统通过51单片机对A/D芯片进行控制,完成从模拟量到数字量的转换,并通过串行数据存储器对采集到的数据进行存储。系统实现了对一段时间内微电流的监测,具有电路简单、数据携带方便、成本低等优点。文中着重对系统中如何将采集到的数据进行存储做了介绍。