Image coding using dual-tree discrete wavelet transform

In this paper, we explore the application of 2-D dual-tree discrete wavelet transform (DDWT), which is a directional and redundant transform, for image coding. Three methods for sparsifying DDWT coefficients, i.e., matching pursuit, basis pursuit, and noise shaping, are compared. We found that noise shaping achieves the best nonlinear approximation efficiency with the lowest computational complexity. The interscale, intersubband, and intrasubband dependency among the DDWT coefficients are analyzed. Three subband coding methods, i.e., SPIHT, EBCOT, and TCE, are evaluated for coding DDWT coefficients. Experimental results show that TCE has the best performance. In spite of the redundancy of the transform, our DDWT _ TCE scheme outperforms JPEG2000 up to 0.70 dB at low bit rates and is comparable to JPEG2000 at high bit rates. The DDWT _TCE scheme also outperforms two other image coders that are based on directional filter banks. To further improve coding efficiency, we extend the DDWT to an anisotropic dual-tree discrete wavelet packets (ADDWP), which incorporates adaptive and anisotropic decomposition into DDWT. The ADDWP subbands are coded with TCE coder. Experimental results show that ADDWP _ TCE provides up to 1.47 dB improvement over the DDWT _TCE scheme, outperforming JPEG2000 up to 2.00 dB. Reconstructed images of our coding schemes are visually more appealing compared with DWT-based coding schemes thanks to the directionality of wavelets.     

Hiding digital watermarks using multiresolution wavelet transform

In this paper, an image accreditation technique by embedding digital watermarks in images is proposed. The proposed method for the digital watermarking is based on the wavelet transform. This is unlike most previous work, which used a random number of a sequence of bits as a watermark and where the watermark can only be detected by comparing an experimental threshold value to determine whether a sequence of random signals is the watermark. The proposed approach embeds a watermark with visual recognizable patterns, such as binary, gray, or color image in images by modifying the frequency part of the images. In the proposed approach, an original image is decomposed into wavelet coefficients. Then, multi-energy watermarking scheme based on the qualified significant wavelet tree (QSWT) is used to achieve the robustness of the watermarking. Unlike other watermarking techniques that use a single casting energy, QSWT adopts adaptive casting energy in different resolutions. The performance of the proposed watermarking is robust to a variety of signal distortions, such as JPEG, image cropping, sharpening, median filtering, and incorporating attacks     

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。     

Embolic Doppler ultrasound signal detection using discrete wavelet transform

Asymptomatic circulating emboli can be detected by Doppler ultrasound. Embolic Doppler ultrasound signals are short duration transient like signals. The wavelet transform is an ideal method for analysis and detection of such signals by optimizing time-frequency resolution. We propose a detection system based on the discrete wavelet transform (DWT) and study some parameters, which might be useful for describing embolic signals (ES). We used a fast DWT algorithm based on the Daubechies eighth-order wavelet filters with eight scales. In order to evaluate feasibility of the DWT of ES, two independent data sets, each comprising of short segments containing an ES (N=100), artifact (N=100) or Doppler speckle (DS) (N=100), were used. After applying the DWT to the data, several parameters were evaluated. The threshold values used for both data sets were optimized using the first data set. While the DWT coefficients resulting from artifacts dominantly appear at the higher scales (five, six, seven, and eight), the DWT coefficients at the lower scales (one, two, three, and four) are mainly dominated by ES and DS. The DWT is able to filter out most of the artifacts inherently during the transform process. For the first data set, 98 out of 100 ES were detected as ES. For the second data set, 95 out of 100 ES were detected as ES when the same threshold values were used. The algorithm was also tested with a third data set comprising 202 normal ES; 198 signals were detected as ES.     

Three-dimensional discrete wavelet transform architectures

The three-dimensional (3-D) discrete wavelet transform (DWT) suits compression applications well, allowing for better compression on 3-D data as compared with two-dimensional (2-D) methods. This paper describes two architectures for the 3-D DWT, called the 3DW-I and the 3DW-II. The first architecture (3DW-I) is based on folding, whereas the 3DW-II architecture is block-based. Potential applications for these architectures include high definition television (HDTV) and medical data compression, such as magnetic resonance imaging (MRI). The 3DW-I architecture is an implementation of the 3-D DWT similar to folded 1-D and 2-D designs. It allows even distribution of the processing load onto 3 sets of filters, with each set performing the calculations for one dimension. The control for this design is very simple, since the data are operated on in a row-column-slice fashion. Due to pipelining, all filters are utilized 100% of the time, except for the start up and wind-down times. The 3DW-II architecture uses block inputs to reduce the requirement of on-chip memory. It has a central control unit to select which coefficients to pass on to the lowpass and highpass filters. The memory on the chip will be small compared with the input size since it depends solely on the filter sizes. The 3DW-I and 3DW-II architectures are compared according to memory requirements, number of clock cycles, and processing of frames per second. The two architectures described are the first 3-D DWT architectures     

An adaptive maximum likelihood receiver for correlatedRayleigh-fading channels

The paper develops a receiver structure for random Gaussian signals in additive noise based on the classic maximum likelihood (M-L), estimator-correlator derivation of Kailath [1960], and applies it to differential phase shift keying (DPSK) on the correlated Rayleigh-fading channel. It is shown to lower the error floor found in the performance of conventional DPSK receivers by orders of magnitude. In addition, the maximum-likelihood procedure is shown to make uncorrelated symbol decisions. The performance of both conventional and optimal receivers, which require knowledge of the channel statistics, is examined analytically. A recursive, channel-adaptive version of the optimal receiver, utilizing decision feedback to estimate the channel statistics, is developed. Its simulated performance shows no penalty compared to theoretical calculations which require explicit knowledge of the channel statistics     

基于导频信号和最大似然估计算法的离散小波包调制的研究

目前,紧张的无线频谱资源已经使频谱利用率成为无线通信系统面临的重要问题。多载波调制技术能有效解决上述问题并以其高效的频谱利用率和良好的抗多径衰落性能成为4G的核心传输技术之一。本文提出一种基于导频信号和最大似然估计算法的离散小波包多载波调制系统。通过对导频信号的设计,获得信道状态信息,利用最大似然估计算出最优信道状态信息,最后利用基于迫零算法消除由多径衰落引起的码间干扰。通过理论分析和仿真验证,基于导频信号和最大似然估计的算法的离散小波包调制是值得考虑的多载波调制技术。     

小波变换和菲涅耳变换的多彩色图像加密

为了解决多彩色图像加密后,解密图像质量不佳、数据量大以及传输时速率慢的问题,采用了一种基于小波变换和菲涅耳变换的多彩色图像加密方法,加密过程中,利用小波变换的多级分解特性提取每幅彩色图像的低频分量,将低频分量分别重组为三元组图像（R,G和B）,并且依次将三元组图像（R,G和B）通过菲涅耳域中的衍射加密系统,对这3个三元组图像进一步加密,从而实现了多彩色图像的加密。结果表明,该方法不仅可以高质量地恢复原始彩色图像,而且可以同时对4幅彩色图像进行加密,提高了加密彩色图像的容量;原始图像经过小波变换,其数据量压缩到原来的1/4,有利于数据的传输和存储。该算法能够有效地同时对多幅色彩图像进行压缩和加密,不仅提高了解密图像的质量,并且具有较高的密钥敏感度和较好的鲁棒性。     

Robust digital watermarking algorithm based on continuous hyperchaotic system and discrete wavelet transform

Many digital watermarking methods have been pro-posedin the last fewyears[1 ,3].It is a tradeoff problemsince whenthe robustness of a watermarkincreases ,theperceptual quality of the contents will be degraded.Hence,the main goal of i mproving a watermarki…     

VLSI implementation of discrete wavelet transform

This paper presents a VLSI implementation of discrete wavelet transform (DWT). The architecture is simple, modular, and cascadable for computation of one or multidimensional DWT. It comprises of four basic units: input delay, filter, register bank, and control unit. The proposed architecture is systolic in nature and performs both high- and low-pass coefficient calculations with only one set of multipliers. In addition, it requires a small on-chip interface circuitry for interconnection to a standard communication bus. A detailed analysis of the effect of finite precision of data and wavelet filter coefficients on the accuracy of the DWT coefficients is presented. The architecture has been simulated in VLSI and has a hardware utilization efficiency of 87.5%. Being systolic in nature, the architecture can compute DWT at a data rate of N×10⁶ samples/s corresponding to a clock speed of N MHz     

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。     

Efficient architectures for two-dimensional discrete wavelet transform using lifting scheme.

Novel architectures for 1-D and 2-D discrete wavelet transform (DWT) by using lifting schemes are presented in this paper. An embedded decimation technique is exploited to optimize the architecture for 1-D DWT, which is designed to receive an input and generate an output with the low- and high-frequency components of original data being available alternately. Based on this 1-D DWT architecture, an efficient line-based architecture for 2-D DWT is further proposed by employing parallel and pipeline techniques, which is mainly composed of two horizontal filter modules and one vertical filter module, working in parallel and pipeline fashion with 100% hardware utilization. This 2-D architecture is called fast architecture (FA) that can perform J levels of decomposition for N * N image in approximately 2N2(1 - 4(-J))/3 internal clock cycles. Moreover, another efficient generic line-based 2-D architecture is proposed by exploiting the parallelism among four subband transforms in lifting-based 2-D DWT, which can perform J levels of decomposition for N * N image in approximately N2(1 - 4(-J))/3 internal clock cycles; hence, it is called high-speed architecture. The throughput rate of the latter is increased by two times when comparing with the former 2-D architecture, but only less additional hardware cost is added. Compared with the works reported in previous literature, the proposed architectures for 2-D DWT are efficient alternatives in tradeoff among hardware cost, throughput rate, output latency and control complexity, etc.     

New realisation of maximum likelihood receiver for low-angle tracking radar

A new realisation of the maximum likelihood receiver is presented for resolving the effect of multipath in a low-angle tracking radar. Results are included to confirm the validity of this receiver structure.     

基于冗余小波变换的高频地波雷达目标检测算法

为了从高频地波雷达(High Frequency Surface Wave Radar, HFSWR)信号生成的复杂距离多普勒(Range Doppler, RD)图像中准确提取运动点目标, 提出了一种基于冗余小波变换(Redundant Discrete Wavelet Transformation, RDWT)的RD图像点目标检测算法.该算法根据点目标与海杂波、电离层杂波等特征的差异, 首先在距离方向进行自适应RDWT以去除海杂波和地杂波, 并在多普勒方向进行自适应RDWT以去除电离层杂波; 然后利用图像形态学运算对背景噪声进行了抑制; 最后进行阈值自适应分割以得到点目标.实验结果表明:该算法能有效抑制RD图像中的海杂波、电离层杂波和背景噪声, 能从复杂的RD图像中实现点目标的有效检测, 其检测性能优于改进的恒虚警率(Constant False Alarm Rate, CFAR)算法.     

Asymptotic receiver structures for joint maximum likelihood timedelay estimation and channel identification using Gaussian signals

The problem of jointly estimating the relative time delay and the impulse response linking two received discrete-time Gaussian signals is addressed. Using two different methods, possible structures for the joint maximum-likelihood (ML) estimator are proposed, when the observation interval is long compared to both the delay to estimate and the correlation time, of the various random processes involved. These structures generalize the cross-correlation method with prefiltering that implements the ML estimation of pure time delays     

Performance comparison of two-dimensional discrete wavelet transform computation schedules on a VLIW digital signal processor

The two-dimensional discrete wavelet transform (2D DWT) is becoming one of the standard tools for image and video compression systems. Various input-traversal schedules have been proposed for its computation. Here, major schedules for 2D DWT computation are compared with respect to their performance on a very long instruction-word (VLIW) digital signal processor (DSP). In particular, three popular transform-production schedules are considered: the row-column, the line based and the block based. Realisations of the wavelet transform according to the considered schedules have been developed. They are parameterised with respect to filter pair, image size and number of decomposition levels. All realisations have been mapped on a VLIW DSP, as these processors currently form an attractive alternative for the realisation of signal, image and video processing systems. Performance metrics for the realisations for a complete set of parameters have been obtained and compared. The experimental results show that each realisation performs better for different points of the parameter space.     

Direction-adaptive discrete wavelet transform for image compression.

We propose a direction-adaptive DWT (DA-DWT) that locally adapts the filtering directions to image content based on directional lifting. With the adaptive transform, energy compaction is improved for sharp image features. A mathematical analysis based on an anisotropic statistical image model is presented to quantify the theoretical gain achieved by adapting the filtering directions. The analysis indicates that the proposed DA-DWT is more effective than other lifting-based approaches. Experimental results report a gain of up to 2.5 dB in PSNR over the conventional DWT for typical test images. Subjectively, the reconstruction from the DA-DWT better represents the structure in the image and is visually more pleasing.     

基于小波变换的硬拷贝全息水印

提出一种基于离散小波变换的硬拷贝数字全息水印方法。首先利用共轭对称延拓傅里叶计算全息生成水印全息图;然后对其进行小波分解,将包含全部水印信息的高频分量嵌入到载体图像小波分解的中频区域以实现信息隐藏。由于全息图的频谱可控性和不可撕毁性,本文全息水印方法具有很好的不可见性,可以实现水印盲提取,不仅能够抵抗剪切、噪声、滤波和...     

Fast text location based on discrete wavelet transform

The paper describes a texture-based fast text location scheme which operates directly in the Discrete Wavelet Transform (DWT) domain. By the distinguishing texture characteristics encoded in wavelet transform domain, the text is fast detected from complex background images stored in the compressed format such as JPEG2000 without full decompress. Compared with some traditional character location methods, the proposed scheme has the advantages of low computational cost, robust to size and font of characters and high accuracy. Preliminary experimental results show that the proposed scheme is efficient and effective.