Wavelet to DCT transcoding in transform domain

Wavelet to DCT transcoding provides inter-operability between standards using the two transforms for encoding. Transcoding in transform domain avoids inverse transform and re-transform operations and saves computation. In this paper, we propose new algorithms for transcoding wavelet coefficients to block DCT coefficients. In the first step, the wavelet coefficients are transformed into upsampled DCT coefficients. Subsequently, these trans-formed coefficients are synthesized in the block DCT space for transcoding. The proposed approach restricts all operations in the DCT domain that makes filtering involved in the synthesis process computationally efficient. The proposed technique could be used by the block DCT based services when the input is available as wavelet coefficients.     

Foveation embedded DCT domain video transcoding

Video transcoding is a key technology to support video communications over heterogeneous networks. Although quite a bit of research effort has been made in video transcoding due to its wide applications, most video transcoding techniques proposed in the literature are optimized based on the simple mean squared error (MSE) metric which does not correlate well with the human visual perception. In this paper, foveation, a property of the HVS, is exploited in video transcoding. The proposed foveation embedded DCT domain video transcoding can reduce the bit rate without compromising visual quality or achieve better subjective quality for a given bit rate by shaping the compression distortion according to the foveated contrast sensitivity function of the HVS. In addition, fast algorithms for video foveation filtering and DCT domain inverse motion compensation are developed, which significantly improve the efficiency of video transcoding.     

基于DCT变换的QWT域改进的图像盲水印算法

针对数字图像的版权保护,基于离散余弦变换和四元数小波变换,提出了一种新的改进的盲水印算法,先根据待嵌入水印的大小对载体图像进行四元数小波变换,获得与幅值和相位信息相对应的4幅低频子带,然后对每个低频子带分别进行全局离散余弦变换,最后通过修改两个随机子带中特定位置上DCT系数的大小关系嵌入水印,利用分阶线性Logistic映射产生的混沌序列预处理经Arnold置乱后的水印信息和确定水印的嵌入位置.实验结果表明,该算法对添加噪声、JPEG压缩、滤波和亮度及对比度调整等攻击都具有很强的鲁棒性.     

Joint image splicing detection in DCT and Contourlet transform domain

Splicing is a fundamental and popular image forgery method and image splicing detection is urgently called for digital image forensics recently. In this paper, a Markov based approach is proposed to detect image splicing. The paper applies the Markov model in the block discrete cosine transform (DCT) domain and the Contourlet transform domain. First, the original Markov features of the inter-block between block DCT coefficients are improved by considering the different frequency ranges of each block DCT coefficients. Then, additional features are extracted in Contourlet transform domain to characterize the dependency of positions among Contourlet subband coefficients. And these features are extracted from single color channel for gray image while extracted from three color channels for color image. Finally, Support Vector Machines (SVMs) are exploited to classify the authentic and spliced images for the gray image dataset while ensemble classifier to the color image dataset. The experiment results demonstrate that the proposed detection scheme outperforms some state-of-the-art methods when applied to Columbia Image Splicing Detection Evaluation Dataset (DVMM), and ranks fourth in phase 1 on the Live Ranking of the first Image Forensics Challenge.     

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。     

一种改进的小波变换阈值去噪方法

Donoho等提出了一种基于小波变换的阈值去噪方法,这种方法在信号去噪及数据压缩等领域得到了广泛的应用。但是,Donoho设计的阈值处理方法对脉冲噪声的抑制效果不明显,因此在脉冲噪声存在的情况下,Donoho的阈值处理方法受到了限制。本文在Donoho方法基础上,设计了一种改进的阈值去噪方法,该方法对一大类的噪声信号有效,特别在保护信号边缘的同时去除脉冲噪声方面表现出了很好的特性。实验结果证实了该方法的有效性。     

Low bit-rate cloud-based image coding in the wavelet transform domain

The rapid growth of image resources on the Internet makes it possible to find some highly correlated images on some Web sites when people plan to transmit an image over the Internet. This study proposes a low bit-rate cloud-based image coding scheme, which utilizes cloud resources to implement image coding. Multiple- discrete wavelet transform was adopted to decompose the input image into a low-frequency sub-band and several high-frequency sub-bands. The low-frequency sub-band image was used to retrieve highly correlated images (HCOIs) in the cloud. The highly correlated regions in the HCOIs were used to reconstruct the high-frequency sub-bands at the decoder to save bits. The final reconstructed image was generated using multiple inverse wavelet transform from a decompressed low-frequency sub-band and reconstructed high-frequency sub-bands. The experimental results showed that the coding scheme performed well, especially at low bit rates. The peak signal-to-noise ratio of the reconstructed image can gain up to 7 and 1.69 dB over JPEG and JPEG2000 under the same compression ratio, respectively. By utilizing the cloud resources, our coding scheme showed an obvious advantage in terms of visual quality. The details in the image can be well reconstructed compared with both JPEG, JPEG2000, and intracoding of HEVC.     

Image compressed sensing based on wavelet transform in contourlet domain

Compressed sensing (CS) has been widely concerned and sparsity of a signal plays a crucial role in CS to exactly recover signals. Contourlet transform provides sparse representations for images, so an algorithm of CS reconstruction based on contourlet is considered. Meanwhile, taking into account the computation and the storage of large random measurement matrices in the CS framework, we are trying to introduce the wavelet transform into the contourlet domain to reduce the size of random measurement matrices. Several numerical experiments demonstrate that this idea is feasible. The proposed algorithm possesses the following advantages: reduced size of random measurement matrix and improved recovered performance.     

Drift controlled scalable wavelet based video coding in the overcomplete discrete wavelet transform domain

Traditional video coders use the previous frame to perform motion estimation and compensation. Though they are less complex and have minimum coding delays, these coders lose their efficiency when subjected to scalability requirements. Recent 3D wavelet coders using lifting schemes offer high compression efficiency and scalability without significant loss in performance. The main drawback of 3D coders is that they process several frames at a time. This introduces additional delay, which makes them less suitable for real time applications.In this work, we propose a novel scheme to minimize drift in scalable wavelet based video coding, which gives a balanced performance between compression efficiency and reconstructed quality with less drift. Our drift control mechanism maintains two frame buffers in the encoder and decoder; one that is based on the base layer and one that is based on the base plus enhancement layers. Drift control is achieved by switching between these two buffers for motion estimation and compensation. Our prediction is initially based on the base plus enhancement layers buffer, which inherently introduces drift in the system if a part of the enhancement layer is not available at the receiver. A measure of drift is computed based on the channel information and a threshold is set. When the measure exceeds the threshold, i.e., when drift becomes significant, we switch the prediction to be based on the base layer buffer, which is always available to the receiver. We also developed an adaptive scheme with additional computation overhead at the encoder to decide the switching instance. The performance of the threshold case that needs fewer computations is comparable with the adaptive scheme. Our coder offers high compression efficiency and sustained video quality for variable bit rate wireless channels. This proves that we need not completely eliminate drift and decrease compression efficiency to get better received video quality.     

Frequency domain volume rendering by the wavelet X-ray transform

We describe a wavelet based X-ray rendering method in the frequency domain with a smaller time complexity than wavelet splatting. Standard Fourier volume rendering is summarized and interpolation and accuracy issues are briefly discussed. We review the implementation of the fast wavelet transform in the frequency domain. The wavelet X-ray transform is derived, and the corresponding Fourier-wavelet volume rendering algorithm (FWVR) is introduced, FWVR uses Haar or B-spline wavelets and linear or cubic spline interpolation. Various combinations are tested and compared with wavelet splatting (WS). We use medical MR and CT scan data, as well as a 3-D analytical phantom to assess the accuracy, time complexity, and memory cost of both FWVR and WS. The differences between both methods are enumerated.     

Image sequence coding using adaptive vector quantisation in wavelet transform domain

A new scheme for image sequence coding using the wavelet transform and adaptive vector quantisation is proposed. The transform is used to decompose an image into multiresolution and multiband sub-images. Adaptive vector quantisation is then applied to achieve image data compression with good quality and low bit rate. Experimental results are presented.<>     

一种小波域改进非局部均值滤波算法

提出了一种噪声图像高效滤波算法。该算法对经典非局部均值滤波算法从边缘保持效果和计算复杂度两个方面加以改进。提出一种基于图像结构相似度(SSIM)相似性检测算子,并将其与传统的高斯加权欧氏距离进行加权融合,从而实现对经典非局部均值滤波的改进,可实现对图像边缘和平坦区域滤波的有效兼顾。将其引入到小波变换域,对于高频子图像,首先采用Canny算子实现自适应边缘检测,获得边缘和非边缘图像,采用改进非局部均值滤波和经典非局部均值滤波分别加以处理,然后实现图像的融合;最后实现小波系数重构。通过对实物图像和标准测试图像的仿真实验结果表明,该滤波算法的去噪效果较优,能基本实现对高强度随机噪声情形下的图像复原,从而印证了该滤波思路的可行性。     

基于混沌映射的小波变换域数字水印算法

本文结合传统的密码学和小波变换域数字水印技术,在水印信息被嵌入到载体作品之前,根据密码学原理将水印进行加密,然后再进行嵌入,充分考虑了小波变换的频域特性与人类视觉系统的很好匹配.在前人的研究基础上,利用图像的小波变换域的JND模型提出了一种基于混沌映射的在图像的小波变换域嵌入数字水印的算法.实验证明,用该算法嵌入的水印...     

小波变换在傅立叶变换轮廓术中的应用

从小波变换本质、原理出发 ,说明它在提取条纹位相方面的应用 ,通过阐述小波变换与傅立叶变换两者之间的内在联系 ,将小波变换应用到傅立叶变换轮廓术中 ,并着重用傅立叶变换的原理对小波提取位相的原理进行详细解释。模拟结果表明 :小波变换在傅立叶变换轮廓术中的应用是正确的、可行的。     

Image extraction in DCT domain

More and more digital images are being stored in compressed formats, among which the format using discrete cosine transform (DCT) coefficients is widely adopted (JPEG, MPEG, H.263 etc). To exploit those successful image processing techniques developed in the pixel domain, the authors propose a fast image extraction algorithm to allow images to be extracted directly from compressed DCT coefficients without full decompression. In the proposed technique the extracted images retain quality comparable with that of fully decoded images. However, the computing cost and the storage expense incurred by the proposed algorithm are very much lower than the costs of full decompression. The experiments also demonstrate that the proposed algorithm has tremendous potential in that all existing image processing techniques developed in the pixel domain can be directly applied to compressed images, without involving full decompression.     

基于关键熵的双树复小波域盲图像水印算法

设计了一种基于关键熵的盲数字图像水印算法.首先,使用尺度不变特征变换(SIFT)方法,从图像中提取特征点;其次,以特征点为中心构造局部不变圆形区域,并对其进行归一化处理;然后,选取大于图像平均熵的图像区域作为关键熵图像区域;最后,结合量化调制策略及双树复小波变换(DTCWT)技术,将水印嵌入到关键熵图像区域中.实验分析...     

An Improved All Zero Block Finding method based on the statistic characteristics of DCT transform coefficients

In the H.263 video codec related systems, motion estimation and Discrete Cosine Transform （DCT） have the most computational requirements. In order to reduce complexity of the encoder to dedicate more resources to other functions, according to the study of existing methods, an Improved All Zero Block Finding （IAZBF） method based on the statistic characteristics of DCT coefficients is proposed. Compared with existing methods, IAZBF improves the detecting efficiency by about 50% without importing too much extra computation requirement. Being computed with additions and shifts instead of complicated multiplications, IAZBF is of low computation complexity, especially for low-end processors. In addition, IAZBF upholds picture fidelity and remains compatible with the H.263 bitstream standard.     

Efficient video watermarking based on singular value decomposition in the discrete wavelet transform domain

This paper presents an efficient, robust, and imperceptible video watermarking technique based on singular value decomposition (SVD) performed in the Discrete Wavelet Transform (DWT) domain. In the proposed DWT-based SVD video watermarking method, the video frames are transformed with the DWT using two resolution levels. The high frequency band HH and the middle frequency bands LH and HL are SVD transformed and the watermark is hidden in them. The proposed DWT-based SVD video watermarking method is characterized by two improvements: (1) a cascade of two powerful mathematical transforms; the Discrete Wavelet Transform (DWT)-based SVD using additive method, and (2) an error correction code is applied and embeds the watermark with spatial and temporal redundancy. The aim of these improvements is to increase robustness against attacks based on video characteristics and the robustness against image processing attacks, realize high security level, protect the watermark against bit errors and obtain good perceptual quality. The proposed DWT-based SVD video watermarking method has been tested in the presence of video and image processing attacks and experimental results proved that the proposed DWT-based SVD video watermarking method survives attacks based on video characteristics and image processing techniques.     

基于DCT变换的噪声估计算法

噪声极大地影响了图像视频处理算法的有效性。提出了一种基于DCT变换的自适应噪声估计算法,其采用DCT系数作为块均匀度的度量,较好地适应了高低噪声的情况。此外,算法复杂度不大,能适用于各种实时图像视频处理系统。     

小波变换域数字图像增强算法及实现

图像增强是数字图像预处理中的重要方法,其主要目的是改善视觉效果.小波变换在图像压缩和图像分割两个方面应用较为广泛,图像增强方面应用较少.现概括了图像增强的原理,阐述了图像增强的方法,分析了一种小波变换域的图像增强算法并在Matlab环境下仿真实现.该算法首先使用haar小波对图像进行2层分解,然后对低频部分进行增强,对高频部分进行衰减,实验结果证明这是对图像去噪和增强的一种有效方法.