Bayesian Wavelet-Based Image Denoising Using the Gauss–Hermite Expansion

The probability density functions (PDFs) of the wavelet coefficients play a key role in many wavelet-based image processing algorithms, such as denoising. The conventional PDFs usually have a limited number of parameters that are calculated from the first few moments only. Consequently, such PDFs cannot be made to fit very well with the empirical PDF of the wavelet coefficients of an image. As a result, the shrinkage function utilizing any of these density functions provides a substandard denoising performance. In order for the probabilistic model of the image wavelet coefficients to be able to incorporate an appropriate number of parameters that are dependent on the higher order moments, a PDF using a series expansion in terms of the Hermite polynomials that are orthogonal with respect to the standard Gaussian weight function, is introduced. A modification in the series function is introduced so that only a finite number of terms can be used to model the image wavelet coefficients, ensuring at the same time the resulting PDF to be non-negative. It is shown that the proposed PDF matches the empirical one better than some of the standard ones, such as the generalized Gaussian or Bessel K-form PDF. A Bayesian image denoising technique is then proposed, wherein the new PDF is exploited to statistically model the subband as well as the local neighboring image wavelet coefficients. Experimental results on several test images demonstrate that the proposed denoising method, both in the subband-adaptive and locally adaptive conditions, provides a performance better than that of most of the methods that use PDFs with limited number of parameters.      

彩色图像数字水印新算法的研究

为了解决电子产品印刷盗版的问题,提出了基于LAB色彩空间和DWT的彩色图像数字水印算法,算法将水印置乱后嵌入到LAB色彩空间的亮度L分量的小波分解系数,实验证明,所提出的算法对常用的图像处理如JPEG压缩、加噪、剪切和滤波等攻击具有较好的鲁棒性、不可见性和安全性.     

A DWT-Based Rational Dither Modulation Scheme for Effective Blind Audio Watermarking

A scheme jointly exploring the rational dither modulation (RDM) and auditory masking properties in the discrete wavelet transform (DWT) domain is proposed to achieve effective blind audio watermarking. The embedding of binary information is carried out by modulating coefficient vectors in the 5th-level approximation subband using the quantization steps estimated from past watermarked vectors. The robustness and payload capacity of the proposed scheme are maneuverable by varying vector dimensions, while the imperceptibility is ensured by constraining quantization noise below the auditory masking threshold. Furthermore, the periodic characteristic inherited in the RDM formulation can be used to re-establish synchronization for accurate watermark extraction. Experimental results show that the proposed DWT–RDM approach renders a near-zero objective difference grade in the perceptual evaluation of audio quality even when the signal-to-noise ratio maintains at a level near 20 dB. In most digital signal processing attacks, the bit error rates of retrieved watermarks are sufficiently low as compared to other recently developed methods with fewer payload capacities.     

Nonlinear Microwave Imaging for Breast-Cancer Screening Using Gauss–Newton's Method and the CGLS Inversion Algorithm

Breast-cancer screening using microwave imaging is emerging as a new promising technique as a supplement to X-ray mammography. To create tomographic images from microwave measurements, it is necessary to solve a nonlinear inversion problem, for which an algorithm based on the iterative Gauss-Newton method has been developed at Dartmouth College. This algorithm determines the update values at each iteration by solving the set of normal equations of the problem using the Tikhonov algorithm. In this paper, a new algorithm for determining the iteration update values in the Gauss-Newton algorithm is presented which is based on the conjugate gradient least squares (CGLS) algorithm. The iterative CGLS algorithm is capable of solving the update problem by operating on just the Jacobian and the regularizing effects of the algorithm can easily be controlled by adjusting the number of iterations. The new algorithm is compared to the Gauss-Newton algorithm with Tikhonov regularization and is shown to reconstruct images of similar quality using fewer iterations.     

Block-Coordinate Gauss–Newton Optimization and Constrained Monotone Regression for Image Registration in the Presence of Outlier Objects

In this paper, we propose the block-coordinate Gauss-Newton/regression method in order to conduct a correlation-based registration considering the intensity difference between images in the presence of outlier objects. In the proposed method, the parameters are decomposed into two blocks, one of which is for the spatial registration and the other for the intensity compensation. The two blocks are sequentially updated by the Gauss-Newton update and the polynomial regression, respectively. Because of the separated blocks, we can perform a joint optimization with low computational complexity and high implementation flexibility. For example, we apply separately appropriate scaling techniques to the parameter blocks for a stable and fast convergence of the algorithm. Furthermore, we apply the constrained monotone regression with a robust outlier detection scheme for the intensity compensation block. From numerical results, it is shown that the proposed algorithm more effectively performs a correlation-based registration considering the intensity difference alleviating the influence of the outlier objects compared to the traditional registration algorithms that perform the joint optimization.     

Discrete Multiwavelet–Based Video Watermarking Scheme Using SURF

This paper proposes a robust, imperceptible block‐based digital video watermarking algorithm that makes use of the Speeded Up Robust Feature (SURF) technique. The SURF technique is used to extract the most important features of a video. A discrete multiwavelet transform (DMWT) domain in conjunction with a discrete cosine transform is used for embedding a watermark into feature blocks. The watermark used is a binary image. The proposed algorithm is further improved for robustness by an error‐correction code to protect the watermark against bit errors. The same watermark is embedded temporally for every set of frames of an input video to improve the decoded watermark correlation. Extensive experimental results demonstrate that the proposed DMWT domain video watermarking using SURF features is robust against common image processing attacks, motion JPEG2000 compression, frame averaging, and frame swapping attacks. The quality of a watermarked video under the proposed algorithm is high, demonstrating the imperceptibility of an embedded watermark.     

一种新的小波域彩色图像水印算法

针对数字产品的版权保护问题,以离散余弦变换（DCT）和奇异值分解（SVD）为基础,提出了一种新的小波域彩色图像数字水印算法。该算法主要是将水印图像的DCT系数以新的方法嵌入到载体图像中低频小波系数分块奇异值分解的奇异值中。实验结果表明了算法的可行性和有效性,并对加噪、滤波、JPEG压缩、剪切等常见的攻击有良好的鲁棒性,具有较好的实用价值。     

用MATLAB实现红外焦平面探测器盲元的统计分析

红外焦平面探测器的盲元分布对红外图像有很大影响.介绍了用MATLAB图像处理工具箱提供的命令实现红外焦平面探测器盲元统计分析的方法.该方法可以很容易得到探测器相连成块盲元的分布情况,具有程序实现简单、工作量小等优点.举例说明了该方法在实际中的应用.     

Image Error Concealment Using Watermarking with Subbands for Wireless Channels

Transmission of block-coded images through error-prone wireless channels often results in lost blocks. In this study, we investigate a novel error concealment method for covering up these high packet losses and reconstructing a close approximation. Our scheme is a modified discrete wavelet transform (DWT) technique (namely, subbands based image error concealment (SIEC)) for embedding downsized replicas of original image into itself. We propose that this technique can be implemented for wireless channels to combat degradations in a backward-compatible scheme. We show that the proposed error concealment technique is promising, especially for the erroneous channels causing a wider range of packet losses, at the expense of computational burden     

基于DCT与SVD相结合的图像水印新算法

基于奇异值分解的水印算法中,利用正交矩阵实现水印的嵌入保证了水印的不可替换性.但在修改正交矩阵时,如果不保持矩阵的正交性,就会对提取出水印的正确率产生影响.为了解决这一问题,提出了一种基于二维离散余弦变换与奇异值分解相结合的数字图像水印新算法.在水印嵌入时,对图像子块的DCT系数矩阵进行SVD分解,利用三角函数的正交性...     

A Comment on “Asymptotically Optimal Detection for Additive Watermarking in the DCT AND DWT Domains”

For original paper, see Nikolaidis and Pitas (IEEE Trans. Image Process., vol.12, no.5, p.563-71, May 2003). Explicit expressions are derived for the Fisher information for the generalized Gaussian noise model considered by Nikolaidis and Pitas     

基于分块DRT的SAR图像线性特征检测

传统的线性检测算法对于弱线性和噪声往往效果不佳,其原因是没有充分利用到象素点之间的潜在线性关系。从脊波(Ridgelet)分析出发,提出了一种基于分块离散脊波变换的SAR图像线性特征提取算法。这样首先对SAR图像进行分块离散脊波变换,在变换域进行阈值选取。这样既可以精确定位线性特征,还可以获得线性特征的斜率。仿真试验表明该方法对线性特征比较明显的SAR图像非常有效。     

A Block-Level Image Tamper Detection Scheme Using Modulus Function Based Fragile Watermarking

Intentional illegitimate modification in any digital image data is one of the general malversations in the existing digital domain. Therefore in this work, the authors have devised a fragile watermarking technique for the localization of illegitimate modifications in the digital image content effectually. The proposed technique detects forged digital image content strongly in the block-level of two successive pixels. This scheme is performed at the block level, where the actual image is partitioned into non-overlapping blocks of size (1?×?2) pixels. Afterward, the block-level authentication code is generated from the MSB of two successive pixels of each block using averaging and modulus operations. The generated authentication code/watermark is encrypted using a logistic-map-based chaotic key series. The encrypted authentication code is embedded into two successive pixels of the corresponding block. Further, any form of forgery in the watermarked image can be detected by comparing its extracted authentication code and regenerated authentication code. The proposed procedure is successfully experienced on a variety of grayscale images, and the experimental results exhibit that watermarked images generated by this scheme are of considerably high quality in terms of PSNR, IF, and SSIM. The proposed method is capable of efficient forgery detection by achieving very high accuracy, NC, and true positive rate while maintaining considerably low false-positive and false-negative rates.

     

用于图像认证的安全可逆水印算法

在图像中嵌入可逆水印时,为了提高水印算法的安全性,采用参数化整数小波并利用位于细节子带整数小波系数的特点,提出了一种安全性高的可逆水印算法.实验结果表明,算法具有水印不可见性好、安全性高及篡改定位准确的特点.     

基于量化的双树复小波变换鲁棒图像水印算法

Conventional quantization index modulation (QIM) watermarking uses the fixed quantization step size for the host signal. This scheme is not robust against geometric distortions and may lead to poor fidelity in some areas of content. Thus, we proposed a quantization-based image watermarking in the dual tree complex wavelet domain. We took advantages of the dual tree complex wavelets (perfect reconstruction,approximate shift invariance, and directional selectivity). For the case of watermark detecting, the probability of false alarm and probability of false negative were exploited and verified by simulation.Experimental results demonstrate that the proposed method is robust against JPEG compression, additive white Gaussian noise (AWGN), and some kinds of geometric attacks such as scaling, rotation, etc.     

Medical Image Noise Reduction Using the Sylvester–Lyapunov Equation

Multiplicative noise is often present in medical and biological imaging, such as magnetic resonance imaging (MRI), Ultrasound, positron emission tomography (PET), single photon emission computed tomography (SPECT), and fluorescence microscopy. Noise reduction in medical images is a difficult task in which linear filtering algorithms usually fail. Bayesian algorithms have been used with success but they are time consuming and computationally demanding. In addition, the increasing importance of the 3-D and 4-D medical image analysis in medical diagnosis procedures increases the amount of data that must be efficiently processed. This paper presents a Bayesian denoising algorithm which copes with additive white Gaussian and multiplicative noise described by Poisson and Rayleigh distributions. The algorithm is based on the maximum a posteriori (MAP) criterion, and edge preserving priors which avoid the distortion of relevant anatomical details. The main contribution of the paper is the unification of a set of Bayesian denoising algorithms for additive and multiplicative noise using a well-known mathematical framework, the Sylvester–Lyapunov equation, developed in the context of the Control theory.      

一种面向内容认证的文档图像半脆弱数字水印算法

提出了一种面向内容认证的文档图像半脆弱数字水印算法,该算法利用DCT变换域低频系数之间的关系生成水印信息,并将水印信息嵌入到矩阵的奇异值中,对文档图像进行认证时,不需要原始载体图像,也不需要额外存储水印信息,是一个完全的盲水印算法.实验表明,该算法具有较好的透明性,对JPEG有损压缩具有较好的鲁棒性;对剪切、替换等恶意篡改表现出脆弱性.该算法达到了半脆弱水印的基本要求,是一个安全且实用的半脆弱数字水印算法.     

应用膨胀算法提取目标的直接定位算法

为了解决被动雷达系统中的多发射源定位问题，提出了一种基于多重信号分类(MUSIC)算法和图像膨胀(IE)算法的直接定位方法。该方法结合了谱分析中的MUSIC思想，通过对接收量测协方差矩阵进行特征分析求解目标的位置。首先，在目标个数未知的前提下，利用Akaike信息准则(AIC)来确定模型阶数；然后，推导了基于MUSIC的定位代价函数；之后，利用图像膨胀算法处理得到的代价函数平面；最后，膨胀处理后的输出为目标个数及目标位置的估计值。提出的算法有效地解决了目标检测及提取的问题，能够确定多个目标的位置坐标，为后续的定位性能分析提供可能性，也保证了算法的完整性。进一步地分析了多个临近目标情况下影响目标提取性能的主要因素。     

一种基于脆弱水印技术的图像认证方法

基于计算全息图编码的水印技术是一种脆弱水印技术,由于其极容易被破坏的特性,非常适合用于图像内容的认证,在图像的认证鉴定的时候,通过比较提取的水印和初始水印的相关性鉴定图像内容的完整性,可以有效防止篡改和对修改图像的欺骗性应用。同时,图像的内容被篡改时,水印信息应该提供图像被伪造的证据。利用计算全息图作为水印,嵌入的水印可能被使用傅里叶变换恢复,进而,宿主图像也能被利用同样的全息模式进行篡改和嵌入水印,为了避免这种弊端,还需要引入加密方法。     

一种有效抵抗裁剪攻击的小波域盲水印算法

该文提出了一种有效抵抗裁剪攻击的小波域盲水印算法,能从小的图像块上检测出水印。首先将图像进行小波变换,选择两个所需要的子带,利用相邻特征平均值和奇偶判决法在两个子带上各自重复内嵌一半水印,在水印检测过程中不需要原始图像。实验结果表明,该算法具有较好的透明性,对各种攻击有较强的鲁棒性,尤其是明显增强了小波域水印在面临裁剪攻击和联合攻击时的鲁棒性。