Complexity-constrained best-basis wavelet packet algorithm forimage compression

The concept of adapted waveform analysis using a best-basis selection out of a predefined library of wavelet packet (WP) bases allows an efficient image representation for the purpose of compression. Image coding methods based on the best-basis WP representation have shown significant coding gains for some image classes compared with methods using a fixed dyadic structured wavelet basis, at the expense however, of considerably higher computational complexity. A modification of the best-basis method, the so-called complexity constrained best-basis algorithm (CCBB), is proposed which parameterises the complexity gap between the fast (standard) wavelet transform and the best wavelet packet basis of a maximal WP library. This new approach allows a `suboptimal' best basis to be found with respect to a given budget of computational complexity or, in other words, it offers an instrument to control the trade-off between compression speed and, coding efficiency. Experimental results are presented for image coding applications showing a highly nonlinear relationship between the rate-distortion performance and the computational complexity in such a way that a relatively small increase in complexity with respect to the standard wavelet basis results in a relatively high rate distortion gain     

Wavelet feature selection for image classification

Energy distribution over wavelet subbands is a widely used feature for wavelet packet based texture classification. Due to the overcomplete nature of the wavelet packet decomposition, feature selection is usually applied for a better classification accuracy and a compact feature representation. The majority of wavelet feature selection algorithms conduct feature selection based on the evaluation of each subband separately, which implicitly assumes that the wavelet features from different subbands are independent. In this paper, the dependence between features from different subbands is investigated theoretically and simulated for a given image model. Based on the analysis and simulation, a wavelet feature selection algorithm based on statistical dependence is proposed. This algorithm is further improved by combining the dependence between wavelet feature and the evaluation of individual feature component. Experimental results show the effectiveness of the proposed algorithms in incorporating dependence into wavelet feature selection.     

基于小波包的故障信号特征提取的研究

讨论了交--交变频调速系统故障诊断的重要性,在当前的检测方法与故障诊断手段研究的基础上,提出了一种改进的小波包算法,并运用该算法对变频调速系统输出电流进行分析.该算法的计算量和占用的存储空间较标准的小波包算法均减少80%.同时,运用基于改进的小波包的频带能量法提取变频调速系统的故障特征,分析了小波包分解层次对特征量提取的影响.经过仿真证明,该方法适用于变频调速系统故障信号的特征量提取.     

一种新的图像边缘检测方法

针对基于空间域或小波变换域图像边缘检测算法提取的边缘只是具有有限方向的问题,该文提出使用具有抛物线型尺度和足够方向消失矩的Contourlet变换来更有效地表示自然图像中的奇异曲线。Contourlet子带比小波子带具有更强的方向性,在其子带上检测系数模极大值,运算复杂度更低。实验结果表明,与基于小波模极大值的图像边缘检测方法相比,该文算法有较低的计算复杂度,所提取的边缘更加逼近图像真实边缘。     

基于双正交小波和边缘加权的图像去噪算法

文中针对现有去噪算法存在的问题,提出了一种基于双正交小波和边缘加权的新的图像去噪算法.该算法对图像进行基于图像移位相关性的自适应二叉分解,研究了白高斯噪声在双正交小波分解下的功率谱,并结合图像的边缘信息,对不同区域的去噪阈值以不同权重加权.实验结果表明,文中算法去噪所得图像的MSE优于小波变换全局阈值去噪,视觉效果明显优于维纳滤波去噪.     

改进的小波包算法及在故障信号特征提取中的应用

分析TDaubechies小波系列的频带特性,针对故障诊断信号特征提取的问题,提出了一种改进的小波包算法,并运用该算法对变频调速系统输出电流进行分析。该算法克服了小波包频谱混叠的缺陷且其计算量和占用的存储空间较标准的小波包算法均减少50%.经过仿真证明,该方法适用于变频调速系统故障信号的特征提取。     

采用阶梯量化优化的SPECK算法研究

通过对图像小波变换系数的分析，根据SPECK算法对较高频子带上重要系数的编码问题，提出了一种采用阶梯量化优化的SPECK 算法QSPECK，以优化SPECK算法的编码效率。即先对小波系数矩阵的较高频子带进行阶梯量化，再对量化后的矩阵进行块编码，最后进行逐次逼近量化获得嵌入式码流。实验证明：此算法优化了编码效率，提高了PSNR值。     

ECG compression method based on adaptive quantization of main wavelet packet subbands

In this study, a new compression algorithm for ECG signal is proposed based on selecting important subbands of wavelet packet transform (WPT) and applying subband-dependent quantization algorithm. To this end, first WPT was applied on ECG signal and then more important subbands are selected according to their Shannon entropy. In the next step, content-based quantization and denoising method are applied to the coefficients of the selected subbands. Finally, arithmetic coding is employed to produce compressed data. The performance of the proposed compression method is evaluated using compression rate (CR), percentage root-mean-square difference (PRD) as signal distortion, and wavelet energy-based diagnostic distortion (WEDD) as diagnostic distortion measures on MIT-BIH Arrhythmia database. The average CR of the proposed method is 29.1, its average PRD is <2.9 % and WEDD is <3.2 %. These results demonstrated that the proposed method has a good performance compared to the state-of-the-art compression algorithms.     

MPEG-4 image transmission using MAP source-controlled channeldecoding

In this paper, we develop an error resilient variant of the MPEG-4 embedded zerotree wavelet coder, suitable for mobile fading channels. The residual redundancy in the compressed bit stream provides implicit error protection through the use of source-controlled channel decoding; no explicit channel coding is used. We propose two slight modifications to the MPEG-4 coder. The first removes the arithmetic coding in the lowest frequency subband so that hidden Markov model-based MAP estimation of both the source index and the channel state can be easily applied. The change in bit rate is negligible, while performance during severe channel fading conditions can be greatly increased. The second modification adds variable length packetization to the compressed bit stream created from the higher frequency subbands. The individual packets are independently decodable. An optional rearrangement of the bits in each packet allows MAP estimation to be applied to these subbands as well. Simulation results show a significant performance improvement for the overall system     

基于小波二重树编码的彩色图像压缩

该文提出了一种利用小波变换对彩色图像进行编码的算法。该算法在对Y,Cr,Cb分量进行小波分解的基础之上,结合人眼视觉系统特性对各子带进行量化,采用全新的二重树编码,有效地对高频子带进行压缩。实验结果表明,本算法实现简单,可达到很好的压缩效果。     

小波图像的膨胀-游程编码算法

提出了一种基于形态膨胀运算和游程编码的新型小波编码器膨胀-游程(Dilation-Run)算法。编码器根据图像小波变换后重要系数的带内聚类特性和重要系数分布的带间相似性,利用数学形态学中的膨胀运算搜索并编码各聚类中的重要系数;同时使用一种高效的游程编码技术对各聚类的种子系数,即膨胀运算起始点的位置进行编码,从而避免了小波图像中非重要系数的逐个编码。编码器算法简单,并且基于位平面实现,因此输出码流具有渐进性。实验结果表明,膨胀-游程算法的性能优于零树小波编码器SPIHT,并能与两种形态学小波编码器MRWD 和SLCCA的性能媲美。对于聚类特性显著的图像,算法的性能则优于上述形态学小波编码器。     

Wavelet transform methods for object detection and recovery

We show that a biorthogonal spline wavelet closely approximates the prewhitening matched filter for detecting Gaussian objects in Markov noise. The filterbank implementation of the wavelet transform acts as a hierarchy of such detectors operating at discrete object scales. If the object to be detected is Gaussian and its scale happens to coincide with one of those computed by the wavelet transform, and if the background noise is truly Markov, then optimum detection is realized by thresholding the appropriate subband image. In reality, the Gaussian may be a rather coarse approximation of the object, and the background noise may deviate from the Markov assumption. In this case, we may view the wavelet decomposition as a means for computing an orthogonal feature set for input to a classifier. We use a supervised linear classifier applied to feature vectors comprised of samples taken from the subbands of an N-octave, undecimated wavelet transform. The resulting map of test statistic values indicates the presence and location of objects. The object itself is reconstructed by using the test statistic to emphasize wavelet subbands, followed by computing the inverse wavelet transform. We show two contrasting applications of the wavelets-based object recovery algorithm. For detecting microcalcifications in digitized mammograms, the object and noise models closely match the real image data, and the multiscale matched filter paradigm is highly appropriate. The second application, extracting ship outlines in noisy forward-looking infrared images, is presented as a case where good results are achieved despite the data models being less well matched to the assumptions of the algorithm.     

一种抗噪的红外图像对比度增强方法

提出一种基于离散平稳小波变换和非线性增益的红外图像对比度增强方法。对红外图像进行离散平稳小波变换后,利用所提出的去噪方法对分辨率较好的各高频子带直接去噪;并利用所提出的非线性增益法结合文中的去噪法对分辨率较差的各高频子带进行增强。实验结果表明,提出的方法在有效地增强红外图像对比度的同时,又能很好地抑制相关噪声。算法在视觉质量上优于传统的反锐化掩膜法、直方图均衡法。     

An equalization algorithm for wavelet packet based modulationschemes

A considerable amount of attention has been given in the literature to the use of wavelets for modulation and equalization. In this correspondence, we present an equalization algorithm for a wavelet packet-based modulation scheme. A nonideal channel can be divided into a set of bands, where each band can be approximated as a simple attenuation and delay channel. Wavelet packets, being narrowband and orthonormal, are a natural choice for realizing such bands. Thus, if the data sequence is used to modulate a set of wavelet packets, the equalization problem reduces to that of determining the delay introduced by the channel for each of the wavelet packets (if the wavelet packets do not overlap in the frequency domain) and possibly a change of sign in the decoded symbols. The attenuation affects the SNR at the output of the demodulator, which in turn affects the correct decoding of the transmitted symbols. A minimum square variance algorithm for adaptively choosing the delay has been proposed. The algorithm uses the statistics of the received sequence to pick the appropriate delay. Simulations have been conducted to study the performance of the equalization algorithm and compare it with that of DFT-based DMT scheme     

基于离散正交小波变换的红外图像去噪方法

提出红外图像去噪方法，将小波变换与广义交叉确认原理相结合，在噪声方差未知的前提下，只利用红外图像的输入数据就可以确定所要求的渐近最优阈值。对红外图像进行离散正交小波变换后，分别对各个分解层的高频子带利用所提出的方法进行迭代去噪，使各个高频子带分别收敛于其最大信噪比。实验结果表明，该方法在有效地去除噪声的同时，能较好地保持红外图像的细节信息。算法在性能指标和视觉质量上均优于Donoho提出的小波阈值去噪方法、Johnstone提出经过调整的小波阈值法和传统的中值滤波法。     

Image quality assessment based on multi-channel regional mutual information

In this paper, a novel method based on multi-channel regional mutual information (RMI) is proposed to assess image quality. In the proposed method, the wavelet transform is firstly used to decompose the image into different frequency subbands to calculate RMI values. Then multi-channel RMI is obtained by weighted sum of RMI values in the various wavelet frequency subbands. The performance of the proposed algorithm is compared with that of such universal assessment methods as peak of signal-to-noise ratio (PSNR) and structure similarity (SSIM). Experimental results demonstrate that the proposed method is highly effective for evaluating image quality and it outperforms the assessment methods based on PSNR and SSIM.     

多光谱可见光图像与高分辨率图像的分维融合

针对遥感图像,提出了一种遥感多光谱可见光图像与遥感高分辨率全色图像融合的小波分维算法.利用小波变换的方向选择}生,对遥感多光谱的1分量和遥感全色图像进行小波分解,进而在不同子带中进行遥感图像融合,低频部分采用基于区域能量的融合算法;高频部分使用21×21的窗口加窗逐点计算分维作为权系数进行融合;最后将得到的灰度融合图像...     

Fast multiresolution motion estimation algorithms for wavelet-based scalable video coding

Motion estimation and compensation in wavelet domain have received much attention recently. To overcome the inefficiency of motion estimation in critically sampled wavelet domain, the low-band-shift (LBS) method and the complete-to-overcomplete discrete wavelet transform (CODWT) method are proposed for motion estimation in shift-invariant wavelet domain. However, a major disadvantage of these methods is the computational complexity. Although the CODWT method has reduced the computational complexity by skipping the inverse wavelet transform and making the direct link between the critically sampled subbands and the shift-invariant subbands, the full search algorithm (FSA) increases it. In this paper, we proposed two fast multiresolution motion estimation algorithms in shift-invariant wavelet domain: one is the wavelet matching error characteristic based partial distortion search (WMEC-PDS) algorithm, which improves computational efficiency of conventional partial distortion search algorithms while keeping the same estimate accuracy as the FSA; another is the anisotropic double cross search (ADCS) algorithm using multiresolution-spatio-temporal context, which provides a significantly computational load reduction while only introducing negligible distortion compared with the FSA. Due to the multiresolution nature, both the proposed approaches can be applied to wavelet-based scalable video coding. Experimental results show the superiority of the proposed fast motion estimation algorithms against other fast algorithms in terms of speed-up and quality.     

一种嵌入可读水印的自适应盲水印算法

本文提出了一种基于DWT的嵌入可读水印的自适应盲水印算法,通过分析图像经离散小波变换后细节子带系数的特性,把细节子带系数的均值和方差作为水印信息的一部分来自适应地修改图像小波分解后某些细节子带的系数值,在满足水印不可感知性的条件下自适应地嵌入水印信息,实现了水印不可感知性和鲁棒性之间的折衷.同时,水印的提取无须求助于原图像,很好的实现了水印的盲检测.这里的水印是一幅有实际意义的二值图像.实验结果和攻击测试表明,本文提出的算法对JPEG/JPEG2000压缩、添加噪声、剪切、像素移位等多种攻击有较强的鲁棒性,同时对直方图均衡化、对比度调整和高斯滤波等图像处理操作也具有一定的抵抗能力.     

基于高阶统计量的小波包去噪在瞬态信号检测中的应用研究

本文提出了一种基于高阶统计量的小波去噪的瞬态信号检测方法,这种检测方法结合了小波包多分辨率分析和高阶量的抗高斯干扰特性,因而优于传统的能量检测方法。仿真研究和实验数据处理结果表明,在较低信噪比时,能量检测失效,本检测方法使得检测工作得以继续。