基于二维Gabor小波的人脸识别算法

该文提出了一种基于二维Gabor小波的人脸识别算法。该算法先对人脸图像进行多分辨率的Gabor小波变换,然后在图像上放置一组网格结点,每个结点用该结点处的多尺度Gabor幅度特征描述,采用主元分析法对每个结点进行去相关、降维,最后形成特征结。把每个特征结作为观测向量,对隐马尔可夫模型进行训练,并把优化的模型参数用于人脸识别。实验结果表明,该方法识别率高,复杂度较低。     

Adaptive Gabor transformation for image processing

An algorithm that computes the Gabor coefficients of an image is presented. An adaptive filter that uses the complex least mean-square algorithm for their computation is proposed, and its numerical characteristics are discussed. It is shown that the filter is stable under certain conditions. Because the Gabor transformation seems to be an excellent tool for image compression, the efficiency of information coding using the Gabor coefficients is investigated and compared with coding that uses the coefficients of the discrete cosine transformation (DCT). Properties of both transformations are discussed.     

CBS: Contourlet-Based Steganalysis Method

An ideal steganographic technique embeds secret information into a carrier cover object with virtually imperceptible modification of the cover object. Steganalysis is a technique to discover the presence of hidden embedded information in a given object. Each steganalysis method is composed of feature extraction and feature classification components. Using features that are more sensitive to information hiding yields higher success in steganalysis. So far, several steganalysis methods have been presented which extract some features from DCT or wavelet coefficients of images. Multi-scale and time-frequency localization of an image is offered by wavelets. However, wavelets are not effective in representing the images in different directions. Contourlet transform addresses this problem by providing two additional properties, directionality and anisotropy. The present paper offers an universal approach to steganalysis called CBS, which uses statistical moments of contourlet coefficients as features for analysis. After feature extraction, a non-linear SVM classifier is applied to classify cover and stego images. The efficiency of the proposed method is demonstrated by experimental investigations. The proposed steganalysis method is compared with two well-known steganalyzers against typical steganography methods. The results showed the superior performance of our method.     

一种基于DCT系数重组的降参考3D视频质量评价方法

针对3D视频质量评价,提出了一种基于离散余弦变 换(DCT)系数重组的降参考质量评价方法。方法主要 包括4D数据集构造、DCT变换与重组和降参考(RR)质量评价3个阶段。在4D数据集构造阶段 ,通过联合视 频的空间域、视点域和时间域信息构造包含3D视频全部信息的4D数据集;在DCT变换与重 组阶段,首 先对数据集进行DCT变换,然后筛选复杂度较高的DCT系数进行重组,得到能够表征3D视 频质量的重 组系数集;在RR质量评价阶段,首先采用广义高斯分布(GGD)函数对重组后DCT系数集的每 个子带进行建模, 然后利用系数距离函数和频率比距离函数评估3D视频质量。实验结果表明,本文提出的方 法与主观评价结果有较好的相关性,符合人类视觉系统(HVS)。     

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.     

Logo extraction using dynamic stochastic resonance

This paper presents a novel technique for watermark (logo) extraction from the distorted watermarked images. The proposed technique is based on the combined discrete wavelet transform (DWT), discrete cosine transform (DCT), and dynamic stochastic resonance (DSR). In this technique, DCT transform is applied to the DWT coefficients of the watermarked image. Later on, variance is calculated from the DCT coefficients, and it is used to tune the DCT coefficient with the help of dynamic double-well system parameters that causes resonance to DCT coefficients. The experimental results have been compared with the existing techniques and were found superior in terms of peak-value-of-signal-to-noise-ratio (PSNR) and correlation coefficient.     

利用Gabor小波系数融合进行图像增强的研究

在传统图像增强技术的基础上,提出了一种基于GABOR小波系数融合的图像增强方法。通过Gabor小波对图像进行滤波,产生八个方向的滤波图像系数,对这些图像系数用求平均值融合方法得到图像边缘图,再融合经传统空域增强方法得到的直方图均衡化图像以产生最终增强的边缘信息以便于分析处理的图像。     

基于DCT的分块自适应量化算法及其用于SAR原始数据压缩

该文提出了一种基于离散余弦变换(DCT)和分块自适应量化相结合的SAR原始数据压缩算法。利用SAR原始数据满足局部平稳高斯随机过程的特点,通过将DCT系数进行重排,并对重排后的系数矩阵进行有效的量化比特分配和分块自适应量化,从而大幅度提高了量化增益。通过对真实SAR原始数据的压缩实验结果表明：该文算法与BAQ算法相比,以相对较低的运算复杂度增加,使图像域的压缩性能指标有了明显提高。     

Utilizing neighborhood coefficient correlation: a new image watermarking technique robust to singular and hybrid attacks

A new blind digital image watermarking algorithm with watermark embedded in discrete cosine transform (DCT) coefficients is presented in this paper. The proposed scheme exploits correlation between DCT coefficients in neighborhood blocks for embedding. The watermark is embedded by modifying two DCT coefficients, one pertaining to a block in which watermark bit (0 or 1) is to be embedded and the other corresponding to the selected neighborhood block. Both the selected coefficients are modified by a modification factor so that the difference between the pair of coefficients is brought to a predefined zone. This difference between two DCT coefficients is used to extract watermark. The proposed technique has been tested for different attacks like JPEG compression, rotation, cropping, filtering, gaussian noise, salt and pepper noise, histogram equalization etc. It has been observed that the scheme is highly robust not only for the above mentioned attacks used singularly, but also for different possible combinations of simultaneous attacks. A comparison of the proposed technique with some state of art existing algorithms reveals that our scheme provides better results in terms of quality of watermarked images, payload and robustness.     

Content Authentication Based on JPEG-to-JPEG Watermarking

A content authentication technique based on JPEG-to-JPEG watermarking is proposed in this paper. In this technique, each 88 block in a JPEG compressed image is first processed by entropy decoding, and then the quantized discrete cosine transform (DCT) is applied to generate DCT coefficients: one DC coefficient and 63 AC coefficients in frequency coefficients. The DCT AC coefficients are used to form zero planes in which the watermark is embedded by a chaotic map. In this way, the watermark information is embedded into JPEG compressed domain, and the output watermarked image is still a JPEG format. The proposed method is especially applicable to content authentication of JPEG image since the quantized coefficients are modified for embedding the watermark and the chaotic system possesses an important property with the high sensitivity on initial values. Experimental results show that the tamper regions are localized accurately when the watermarked JPEG image is maliciously tampered.     

Content Authentication Based on JPEG-to-JPEG Watermarking

A content authentication technique based on JPEG-to-JPEG watermarking is proposed in this paper. In this technique, each 8x8 block in a JPEG compressed image is first processed by entropy decoding, and then the quantized discrete cosine transform （DCT） is applied to generate DCT coefficients： one DC coefficient and 63 AC coefficients in frequency coefficients. The DCT AC coefficients are used to form zero planes in which the watermark is embedded by a chaotic map. In this way, the watermark information is embedded into JPEG compressed domain, and the output watermarked image is still a JPEG format. The proposed method is especially applicable to content authentication of JPEG image since the quantized coefficients are modified for embedding the watermark and the chaotic system possesses an important property with the high sensitivity on initial values. Experimental results show that the tamper regions are localized accurately when the watermarked JPEG image is maliciously tampered.     

Rotation-Invariant Texture Classification Using Circular Gabor Wavelets Based Local and Global Features

Rotation-invariant texture classification is one of the most challenging problems in computer vision. This paper presents a new and effective method for rotation-invariant texture classification based on the circular Gabor wavelets. The Gabor representation has been shown to be optimal in the sense of minimizing the joint two-dimensional uncertainty in space and frequency. The circular Gabor filter is completely circularly symmetric. So, the circular Gabor wavelets are constructed to decompose an image into multiple scales （subbands） and are rotation invariant. Two group features can be constructed by the mean and variance of the circular Gabor filtered images, and rotation invariant. The experimental results show that the proposed method has comparatively high correct classification rates.     

基于DCT的实值离散Gabor变换

该文提出了一种基于离散余弦变换(DCT)的实值离散Gabor变换(RDGT),不仅适用于临界抽样条件而且适用于过抽样条件,并证明了变换的完备性条件。由于这种变换仅涉及实值计算,并且可利用快速DCT,IDCT算法来加速运算,因此比传统复值离散Gabor变换在计算和实现方面更为简单,必将有效地提高非平稳信号与图像的分析、处理速度和效率。     

Block-based frequency scalable technique for efficient hierarchical coding

In this paper, we propose a block-based frequency scalable technique for efficient hierarchical coding. The proposed technique divides an image into its multiple resolution versions, based on the spectral properties of discrete cosine transform (DCT) kernels. We present that spectral decomposition, downsampling, and DCT operations are performed effectively over input DCT coefficients of one-dimensional (1-D) and two-dimensional (2-D) signals by using the proposed transform matrices. The proposed image coder is observed to reduce the computational complexity and the memory buffer size with a higher peak signal-to-noise ratio (PSNR), when compared with the traditional hierarchical image coder. In addition, the proposed architecture can preserve compatibility easily with the previous DCT-based image coder.     

基于图像统计特性的二维形态小波的构造

根据图像内部相关性和相邻像素之间的统计信息,本文构造了一种基于图像统计特性的二维形态小波变换,图像经该方法分解后,高频子带能以较大的概率等于零.在图像无损压缩试验中,实验结果表明,与经典的形态小波变换算法相比,图像经本文算法分解后,高频子带的熵更低,高频子带系数中的零元素也更多,取得了好的分析结果.     

Block DCT to wavelet transcoding in transform domain

The Discrete Cosine Transform (DCT) to wavelet transcoding provides input for several wavelet-based post-processing techniques of the DCT-coded image/video signals. Transcoding in domain transform avoids inverse transform and retransform operations and saves computation. In this paper, we propose a new technique for transcoding the DCT blocks to wavelet coefficients directly in the transform domain. We perform filtering, IDCT and downsampling operations in a single combined step. The proposed technique achieves the same computational result as that of a spatial domain technique. The transcoding matrices used in the proposed technique are found to satisfy certain symmetric and sparse properties, which are exploited to reduce the computational cost. As the number of zeros in the DCT coefficients is significantly higher compared to the spatial domain, computational cost reduces significantly. Also, with the proposed technique, it is possible to speedup the operation by ignoring some elements in the filtering matrices whose magnitudes are smaller than a threshold value. We demonstrate the application of the proposed transcoding for deblocking of the DCT-coded images in wavelet domain.     

Novel DCT-Based Real-Valued Discrete Gabor Transform and Its Fast Algorithms

The oversampled Gabor transform is more effective than the critically sampled one in many applications. The biorthogonality relationship between the analysis window and the synthesis window of the Gabor transform represents the completeness condition. However, the traditional discrete cosine transform (DCT)-based real-valued discrete Gabor transform (RGDT) is available only in the critically sampled case and its biorthogonality relationship for the transform has not been unveiled. To bridge these important gaps, this paper proposes a novel DCT-based RDGT, which can be applied in both the critically sampled case and the oversampled case, and their biorthogonality relationships can be derived. The proposed DCT-based RDGT involves only real operations and can utilize fast DCT algorithms for computation, which facilitates computation and implementation by hardware or software as compared to that of the traditional complex-valued discrete Gabor transform. This paper also develops block time-recursive algorithms for the efficient and fast computation of the RDGT and its inverse transform. Unified parallel lattice structures for the implementation of these algorithms are presented. Computational complexity analysis and comparisons have shown that the proposed algorithms provide a more efficient and faster approach for discrete Gabor transforms as compared to those of the existing discrete Gabor transform algorithms. In addition, an application in the noise reduction of the nuclear magnetic resonance free induction decay signals is presented to show the efficiency of the proposed RDGT for time-frequency analysis.      

多尺度Gabor小波变换在图像检索中的应用

在基于内容的图像检索中,纹理特征是一种重要而又难以描述的特征。为提高图像检索中纹理特征的提取效率,通过对Gabor滤波器滤波特点的研究,提出一种基于多尺度Gabor小波纹理的图像检索方法。设计了一组具有多种尺度和多个方向的滤波器组,选择并优化滤波器组的各参数,对图像进行滤波和特征提取。设计并实现了一个基于Gabor纹理...     

Robust facial landmarking for registration

Finding landmark positions on facial images is an important step in face registration and normalization, for both 2D and 3D face recognition. In this paper, we inspect shortcomings of existing approaches in the literature and compare several methods for performing automatic landmarking on near-frontal faces in different scales. Two novel methods have been employed to analyze facial features in coarse and fine scales successively. The first method uses a mixture of factor analyzers to learn Gabor filter outputs on a coarse scale. The second method is a template matching of block-based Discrete Cosine Transform (DCT) features. In addition, a structural analysis subsystem is proposed that can determine false matches, and correct their positions.     

基于Gabor小波变换的人脸表情识别

在人脸表情识别中,针对Gabor小波变换特征维数很大的问题,提出了一种新的多方向特征编码方法。通过对Gabor特征幅值进行统计处理,将每个像素点同一尺度不同方向的Gabor特征幅值闽值化成二进制,加强了Gabor小波对图像局部结构信息的表征。同时,结合了类似旋转不变LBP的方法对图像进行降维。为了进一步提高表情的正确识别率,采用一种局部区域融合的方法,最后在JAFFE表情库上进行测试,得到比较好的识别率,验证了所提方法的有效性。