新颖的基于小波变换的数字水印方案

随着计算机网络技术与多媒体技术的快速发展,数字产品的版权保护已经成为信息技术领域中最重要的问题之一,提出了一种新颖的基于离散小波变换的数字水印方案,该方案利用改进的Pacthwork算法,将水印嵌入到LL子带中,水印信号在解码过程中无需使用原始图像可快速地重嵌入,该算法利用BCH码来降低误码率,应用所提出的算法,把一个32个字符的水印嵌入到图像中,实现结果表明水印是不可察觉的,经过JPEG有损压缩,低通与中值滤波等图像处理操作后仍是鲁棒的。     

Fresnelets: new multiresolution wavelet bases for digital holography

We propose a construction of new wavelet-like bases that are well suited for the reconstruction and processing of optically generated Fresnel holograms recorded on CCD-arrays. The starting point is a wavelet basis of L/sub 2/ to which we apply a unitary Fresnel transform. The transformed basis functions are shift-invariant on a level-by-level basis but their multiresolution properties are governed by the special form that the dilation operator takes in the Fresnel domain. We derive a Heisenberg-like uncertainty relation that relates the localization of Fresnelets with that of their associated wavelet basis. According to this criterion, the optimal functions for digital hologram processing turn out to be Gabor (1948) functions, bringing together two separate aspects of the holography inventor's work. We give the explicit expression of orthogonal and semi-orthogonal Fresnelet bases corresponding to polynomial spline wavelets. This special choice of Fresnelets is motivated by their near-optimal localization properties and their approximation characteristics. We then present an efficient multiresolution Fresnel transform algorithm, the Fresnelet transform. This algorithm allows for the reconstruction (backpropagation) of complex scalar waves at several user-defined, wavelength-independent resolutions. Furthermore, when reconstructing numerical holograms, the subband decomposition of the Fresnelet transform naturally separates the image to reconstruct from the unwanted zero-order and twin image terms. This greatly facilitates their suppression. We show results of experiments carried out on both synthetic (simulated) data sets as well as on digitally acquired holograms.     

Comparison of interpolation and extrapolation methods with a method using multiresolution wavelet transform in dosimetric experiments

International and national organizations have recommended limits for the protection of mobile phone users and standards are going to be established to certify the compliance of mobile phone with these limits. To ensure this conformity, numerical and experimental dosimetric analyses are essential to evaluate the electric field in the user’s head. The use of interpolation and extrapolation is then necessary to evaluate the electric fields components which cannot be measured. In this paper, an interpolation/extrapolation method using wavelets is presented. This method is applied to one, two, and three-dimensional sampled data from dosimetric experiments and compared with other interpolation/extrapolation techniques.     

A maximum likelihood digital receiver using coordinate ascent andthe discrete wavelet transform

In this paper, a maximum likelihood (ML) method is presented for joint estimation of amplitude, phase, time delay, and data symbols in a single-user direct-sequence spread-spectrum communication system. Since maximization of the likelihood function is analytically intractable, a novel coordinate ascent algorithm is used to obtain sequential updates of the data symbols and all unknown nuisance parameters. The novelty of the algorithm is due to the use of a multiresolution expansion of the received signal and the use of polynomial rooting in the complex plane in place of a line search over the signal delay parameter. The multiresolution structure of the algorithm is exploited to reduce sensitivity to impulsive noise via wavelet thresholding. Computer simulations of the single-user system show that the algorithm has fast convergence, and comparison with theoretical lower bounds establishes that the algorithm achieves nearly optimal error performance     

An enhanced approach in video watermarking with multiple watermarks using wavelet

Watermarking technology is an effective method to clarify the problem of protecting multimedia information. It is the expertise of concealing the information into a host such that the embedded data is invisible. In our strategy luminance band of the selected frames is taken further, it is grouped to alternative pixel shares and flip those images. Two color watermark images are split into distinctive pieces and concatenate its layers, further it is embedded into respective flipped shares under wavelet. Unfold the shares into normal image and stack the designations into single luminance layers. Results achieved the quality of the watermarked frame is high and also the concealed data is requested with acceptably by the human visual system which makes them undetectable. Extraction guarantees that the watermark could be effectively recaptured from a quite short portion of the video. Disguised data are less discernible as well as strong against regular video processing attacks.     

Image coding using wavelet transform

A scheme for image compression that takes into account psychovisual features both in the space and frequency domains is proposed. This method involves two steps. First, a wavelet transform used in order to obtain a set of biorthogonal subclasses of images: the original image is decomposed at different scales using a pyramidal algorithm architecture. The decomposition is along the vertical and horizontal directions and maintains constant the number of pixels required to describe the image. Second, according to Shannon's rate distortion theory, the wavelet coefficients are vector quantized using a multiresolution codebook. To encode the wavelet coefficients, a noise shaping bit allocation procedure which assumes that details at high resolution are less visible to the human eye is proposed. In order to allow the receiver to recognize a picture as quickly as possible at minimum cost, a progressive transmission scheme is presented. It is shown that the wavelet transform is particularly well adapted to progressive transmission.     

一种基于小波变换的灰度数字水印嵌入技术

根据图像小波变换后小波系数的特点,提出了一种新的数字水印嵌入技术。该方法所嵌入的不再是传统的数值序列和二值图像,而是把一幅64×64×8bit的图像作为水印信息嵌入到图像中。实验证明,该水印具有较好的透明性和较好的顽健性。     

Hidden digital watermarks in images

An image authentication technique by embedding digital "watermarks" into images is proposed. Watermarking is a technique for labeling digital pictures by hiding secret information into the images. Sophisticated watermark embedding is a potential method to discourage unauthorized copying or attest the origin of the images. In our approach, we embed the watermarks with visually recognizable patterns into the images by selectively modifying the middle-frequency parts of the image. Several variations of the proposed method are addressed. The experimental results show that the proposed technique successfully survives image processing operations, image cropping, and the Joint Photographic Experts Group (JPEG) lossy compression.     

Multiscale video representation using multiresolution motioncompensation and wavelet decomposition

A multiscale video representation using wavelet decomposition and variable-block-size multiresolution motion estimation (MRME) is presented. The multiresolution/multifrequency nature of the discrete wavelet transform makes it an ideal tool for representing video sources with different resolutions and scan formats. The proposed variable-block-size MRME scheme utilizes motion correlation among different scaled subbands and adapts to their importance at different layers. The algorithm is well suited for interframe HDTV coding applications and facilitates conversions and interactions between different video coding standards. Four scenarios for the proposed motion-compensated coding schemes are compared. A pel-recursive motion estimation scheme is implemented in a multiresolution form. The proposed approach appears suitable for the broadcast environment where various standards may coexist simultaneously     

Robust digital watermarks for audio signals

An algorithm of embedding the digital watermarks into speech signals transmitted through analog channels of VHF radio telephony of the maritime and aeronautical mobile services has been designed. For embedding DWM it was proposed to use the vector quantization of the complex envelope of narrow-band signal. DWM robustness to the intersymbol interference, multiplicative and additive interferences is provided, respectively, by the following means: 1) formation of narrow-band channels, 2) step-size adaptation in the transmitter and receiver, and 3) distribution of DWM energy over L samples. This algorithm makes it possible to implement the automatic identification of radiotelephone transmissions without the replacement of the standard radio communication equipment and variation of the operation procedures of radio telephony.     

Rotation-invariant multiresolution texture analysis using radon and wavelet transforms.

A new rotation-invariant texture-analysis technique using Radon and wavelet transforms is proposed. This technique utilizes the Radon transform to convert the rotation to translation and then applies a translation-invariant wavelet transform to the result to extract texture features. A kappa-nearest neighbors classifier is employed to classify texture patterns. A method to find the optimal number of projections for the Radon transform is proposed. It is shown that the extracted features generate an efficient orthogonal feature space. It is also shown that the proposed features extract both of the local and directional information of the texture patterns. The proposed method is robust to additive white noise as a result of summing pixel values to generate projections in the Radon transform step. To test and evaluate the method, we employed several sets of textures along with different wavelet bases. Experimental results show the superiority of the proposed method and its robustness to additive white noise in comparison with some recent texture-analysis methods.     

Texture segmentation using modulated wavelet transform

The wavelet (packet) transform has been widely used for texture analysis; however, the extracted features of similar textures with symmetric orientations are indistinguishable. Motivated by the AM-FM representation, the so called modulated wavelet (packet) transform that can be implemented efficiently by the conventional pyramid (tree) structured algorithms is developed. The performance of this new transform is demonstrated on the segmentation of Brodatz (1966) textures and an aerial image of San Francisco.     

Two-dimensional phase unwrapping using wavelet transform

A method for solving the least squares two-dimensional phase unwrapping problem is presented. This technique is based on the multiresolution representation of a linear system using the discrete wavelet transform. By applying the wavelet transform to the original system, a better convergence condition of an equivalent new system can be achieved     

A study on image digital watermarking based on wavelet transform

This paper studies the methods of image digital watermarking based on wavelet transform. Firstly, the characteristics of image digital watermarking as well as its processing procedure are introduced. On this basis, the discrete wavelet transform (DWT) is selected to achieve the embedding and distilling of image digital watermarking. Simulation test proves that this algorithm can embed or distill digital watermark effectively. Meanwhile it also proves that this watermark has better abilities of hiding and anti-interference. This method results in significant amount of computational savings as well.     

基于小波变换的高精度旋转变压器信号数字转换电路

针对旋转变压器信号到数字转换方法中,在采用DSP处理或查表方法时,由于正弦信号的非线性,造成转换精度较低的问题。本文提出基于小波变换的多分辨率分析理论,设计出一种高精度旋转变压器器信号到数字信号转换电路以提高转换精度。这里通过模拟电路实现Harr小波变换,通过对正弦信号进行逐级逼近处理,将信号分解并平移到（0~π16）范围内,根据泰勒定理实现角度值的求解,实现0.02°（14位二进制精度）的转换精度。成功解决了由于非线性信号造成的旋转变压器器信号到数字信号转换精度较低的问题,具有很高的实用价值。在此分析了电路工作原理并给出了SPICE仿真结果,试验表明该电路能够实现14位的转换精度。     

基于小波变换的数字水印技术的研究

随着数字产品的发展,其知识产权、隐蔽标识等信息越来越重要,数字水印技术这一新型的信息隐藏技术的研究也被予以高度的重视和支持。结合当前国内外水印技术的研究现状,本文以matlab程序语言为基础,在现有的技术基础上,着重研究了一种基于小波域的水印算法,在小波域中实现水印的隐藏与提取。实验证明,这种水印技术能够有效的保护数字图像信息安全和信息隐蔽性,具有一定的推广价值。     

Multiscale corner detection by using wavelet transform

A multiscale corner detection algorithm based on the wavelet transform of contour orientation is proposed. It can utilize both the information of the local extrema and modulus of transform results to detect corners and arcs effectively. The ramp-width of contour orientation profile, which can be computed using the transformed modulus of two scales, reveals the difference between corner and arc and is utilized in the determination of corner points. The experimental results have shown that the detector is more effective than both the single- and multiple-scale detectors. They also demonstrate that the detector is insensitive to boundary noise. In addition, the proposed method is more efficient than the other multiscale corner detector because it operates on fewer number of scales, which can be implemented by a fast transform algorithm.     

Motion estimation using a complex-valued wavelet transform

This paper describes a new motion estimation algorithm that is potentially useful for both computer vision and video compression applications. It is hierarchical in structure, using a separable two-dimensional (2-D) discrete wavelet transform (DWT) on each frame to efficiently construct a multiresolution pyramid of subimages. The DWT is based on a complex-valued pair of four-tap FIR filters with Gabor-like characteristics. The resulting complex DWT (CDWT) effectively implements an analysis by an ensemble of Gabor-like filters with a variety of orientations and scales. The phase difference between the subband coefficients of each frame at a given subpel bears a predictable relation to a local translation in the region of the reference frame subtended by that subpel. That relation is used to estimate the displacement field at the coarsest scale of the multiresolution pyramid. Each estimate is accompanied by a directional confidence measure in the form of the parameters of a quadratic matching surface. The initial estimate field is progressively refined by a coarse-to fine strategy in which finer scale information is appropriately incorporated at each stage. The accuracy, efficiency, and robustness of the new algorithm are demonstrated in comparison testing against hierarchical implementations of intensity gradient-based and fractional-precision block matching motion estimators     

Image compression using wavelet transform and multiresolutiondecomposition

Schemes for image compression of black-and-white images based on the wavelet transform are presented. The multiresolution nature of the discrete wavelet transform is proven as a powerful tool to represent images decomposed along the vertical and horizontal directions using the pyramidal multiresolution scheme. The wavelet transform decomposes the image into a set of subimages called shapes with different resolutions corresponding to different frequency bands. Hence, different allocations are tested, assuming that details at high resolution and diagonal directions are less visible to the human eye. The resultant coefficients are vector quantized (VQ) using the LGB algorithm. By using an error correction method that approximates the reconstructed coefficients quantization error, we minimize distortion for a given compression rate at low computational cost. Several compression techniques are tested. In the first experiment, several 512x512 images are trained together and common table codes created. Using these tables, the training sequence black-and-white images achieve a compression ratio of 60-65 and a PSNR of 30-33. To investigate the compression on images not part of the training set, many 480x480 images of uncalibrated faces are trained together and yield global tables code. Images of faces outside the training set are compressed and reconstructed using the resulting tables. The compression ratio is 40; PSNRs are 30-36. Images from the training set have similar compression values and quality. Finally, another compression method based on the end vector bit allocation is examined.     

Spike detection using the continuous wavelet transform

This paper combines wavelet transforms with basic detection theory to develop a new unsupervised method for robustly detecting and localizing spikes in noisy neural recordings. The method does not require the construction of templates, or the supervised setting of thresholds. We present extensive Monte Carlo simulations, based on actual extracellular recordings, to show that this technique surpasses other commonly used methods in a wide variety of recording conditions. We further demonstrate that falsely detected spikes corresponding to our method resemble actual spikes more than the false positives of other techniques such as amplitude thresholding. Moreover, the simplicity of the method allows for nearly real-time execution.