Directional textures auto-inspection using discrete cosine transform

This paper describes a global image restoration scheme using a discrete cosine transform (DCT) that can be used to detect defects in directional textured surfaces automatically. The input spatial domain image is first transformed into the DCT domain so that the dominant directions of the texture in the input image will be compacted into the orthogonal straight lines or impulses through the direct current (DC) component of the spectrum. The linear primitives associated with the high-energies in the DCT domain are eliminated by reducing them to zero before transforming back to the spatial domain. Finally, the defects, if any, are extracted by the thresholding method. Experiments on a variety of product surfaces with directional textures such as straight, slanted, orthogonal, slanted orthogonal, and oblique linear primitives were conducted in this paper. The proposed scheme would blur directional textures and preserved only local defects if they were initially embedded in the image. Furthermore, some preliminary experiments were also conducted to demonstrate the proposed scheme was insensitive to horizontal and vertical shifting, changes in illumination, and image rotation.     

Low-power differential coefficients-based FIR filters using hardware-optimised multipliers

A minimal-difference differential coefficients method is presented for low power and high-speed realisation of differential-coefficients-based finite impulse response filters. The conventional differential coefficients method (DCM) uses the difference between adjacent coefficients whereas we identify the coefficients that have the least difference between their magnitude values and use these minimal difference values to encode the differential coefficients. Our minimal-difference differential coefficients can be coded using fewer bits, which in turn reduces the number of full additions required for coefficient multiplication. By employing a differential-coefficient partitioning algorithm and a pseudofloating-point representation, we show that the number of full adders and the net memory needed to implement the coefficient multipliers can be significantly reduced. The proposed method is combined with common subexpression elimination for further reduction of complexity. Experimental results show the average reductions of full adder, memory and energy dissipated achieved by our method over the DCM are 40, 35 and 50%, respectively     

Low-power and high-quality Cordic-based Loeffler DCT for signal processing

A computationally efficient and high-quality preserving discrete cosine transform (DCT) architecture is presented. It is obtained by optimising the Loeffler DCT based on the coordinate rotation digital computer (Cordic) algorithm. The computational complexity is reduced significantly from 11 multiply and 29 add operations (Loeffler DCT) to 38 add and 16 shift operations (i.e. similar to the complexity of the binDCT) without losing quality. After synthesising with TSMC 0.13-mum technology library, Synopsys PrimePower was used to estimate the power consumption at gate-level. The experimental results show that the proposed 8-point one-dimensional DCT architecture only consumes 19% of the area and about 16% of the power of the original Loeffler DCT. Moreover, it also retains the good transformation quality of the original Loeffler DCT. In this regard, the proposed Cordic-based Loeffler DCT is very suitable for low-power and high-quality encoder/decoders (codecs) used in battery-based systems.     

Digital color image watermarking based on phase-shifting interferometry and neighboring pixel value subtraction algorithm in the discrete-cosine-transform domain

A novel single-channel color-image watermarking with digital-optics means based on phase-shifting interferometry (PSI) and a neighboring pixel value subtraction algorithm in the discrete-cosine-transform (DCT) domain is proposed. The converted two-dimensional indexed image matrix from an original color image is encrypted to four interferograms by a PSI and double random-phase encoding technique. Then the interferograms are embedded in one chosen channel of an enlarged color host image in the DCT domain. The hidden color image can be retrieved by DCT, the improved neighboring pixel value subtraction algorithm, an inverse encryption process, and color image format conversion. The feasibility of this method and its robustness against some types of distortion and attacks from the superposed image with different weighting factors are verified and analyzed by computer simulations. This approach can avoid the cross-talk noise due to direct information superposition, enhance the imperceptibility of hidden data, and improve the efficiency of data transmission.     

Medical images compression for remote diagnosis using modified SPIHT data organization and fidelity enhancement filter

In this work, an 8 × 8 Discrete Cosine Transform (DCT) approach is adopted to perform DCT shrinkage, followed by modified set partitioning in hierarchical trees (SPIHT) data organization and fidelity enhancement filter for reducing the memory required to store a remote diagnosis and rapidly transmit it. The DCT shrinkage has the ability to retain the detailed characteristics of an image. By means of a simple transformation to gather the DCT spectrum data with the same frequency domain, the DCT shrinkage exploits all the characteristics of individual blocks to a global framework. In this scheme, insignificant DCT coefficients that correspond to the same spatial location in the high‐frequency sub‐bands can be used to reduce the redundancy by a combined function proposed in association with the modified SPIHT. Meanwhile, quad‐tree decomposition and a set of morphological filters for reducing the artifacts are presented. This set of filters employs 8 predefined morphological operations, namely 4 structuring elements (SE), each of which includes both dilation and erosion operations. The voting strategy is used to select the most suitable morphological filter for each block. Simulation results show that the image compression reduced the computational complexity to only a half of the wavelet based sub‐band decomposition and improved the quality of the reconstructed medical image in terms of both the peak signal‐to‐noise ratio (PSNR) and the perceptual results close to JPEG2000 and the original SPIHT at the same bit rate. © 2007 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 17, 49–61, 2007     

Research on 3D integer SDCT transform and quantisation

Abstract

Nowadays, the 3D discrete cosine transform (DCT) is applied widely in video coding. But the transform matrix of DCT is expressed with floating-point numbers, so the computational complexity is high, and more system resources are occupied. In addition, the 3D DCT is accomplished by operating 1D DCT to the rows, columns and pages of 3D data successively, which cannot embody the overall space performance of 3D transform well. To overcome these drawbacks, 3D integer submatrix discrete cosine transform (SDCT) method was proposed in the paper. First, several matrix operation methods were defined. Then, the basic principle and calculation method of 3D integer SDCT was deduced in detail. The main idea was to take the 3D data as a whole, and adopt the integer transform matrix instead of the floating-point transform matrix. Finally, the performances of 3D integer DCT operation were analysed, and the experimental results show that the transform effects based on 3D integer SDCT and 3D DCT are very similar.     

SVD-based digital image watermarking using adaptive generated watermark

In this paper, an evolutionary-based algorithm for digital image watermarking is proposed. Robustness and imperceptibility are two important properties of digital image watermarking which conflict with each other. A singular value decomposition (SVD)-based intelligent algorithm is applied to make a trade-off between robustness and imperceptibility. In the proposed algorithm, first, the original image is divided into 8×8 blocks. Then some special blocks are transformed into discrete cosine transform (DCT) domain. SVD decomposition of DCT coefficients of special blocks is the next stage of the method. Finally, a binary watermark image is embedded into the singular values by a quantisation method. The major property of the proposed method is the generation of a binary watermark image using genetic algorithm to solve the optimisation problem between robustness and imperceptibility. So the watermark could be variable and image adaptive. The simulation results show improvement in robustness of the proposed method against several attacks such as noise contamination, filtering, joint photographic experts group (JPEG) compression and some geometrical attacks like cropping, rotation and rescaling in comparison with a recently similar existing work.     

Rotation-invariant fingerprint matching using radon and DCT

A new set of promising rotation-invariant features based on radon and discrete cosine transform (DCT) is proposed for fingerprint matching. The radon and DCT of a tiny area in the region of core point of fingerprint image is computed. In the proposed method only 34% DCT coefficients are used for feature extraction. Competency of this approach is tested on standard databases, namely FVC2002 and FVC2004. This approach provides 70% genuine acceptance rate (GAR) at ~0% false acceptance rate (FAR) and 95% GAR at 10% FAR on rotated and non-rotated databases, respectively. Experimental results prove that the proposed feature extraction approach is rotation invariant.     

Image compression and encryption scheme with hyper-chaotic system and mean error control

Based on a hyper-chaotic system, an image compression and encryption scheme is presented by adopting mean error control to improve the quantization compression performance of the discrete cosine transform (DCT) coefficients. The transform coefficients of DCT forming a structure similar to the sub-band can be classified and encoded. Then the image is scanned with Zigzag operation in different directions to achieve sufficiently scrambled effects. The cyclic shift matrix for image encryption is generated by the hyper-chaotic system. The four initial inputs for generating the cyclic shift matrix serve as the key. Simulation results demonstrate the security and the effectiveness of the proposed image compression and encryption scheme.     

Magnetic resonance image denoising using nonlocal maximum likelihood paradigm in DCT‐framework

The data acquired by magnetic resonance (MR) imaging system are inherently degraded by noise that has its origin in the thermal Brownian motion of electrons. Denoising can enhance the quality (by improving the SNR) of the acquired MR image, which is important for both visual analysis and other post processing operations. Recent works on maximum likelihood (ML) based denoising shows that ML methods are very effective in denoising MR images and has an edge over the other state‐of‐the‐art methods for MRI denoising. Among the ML based approaches, the Nonlocal maximum likelihood (NLML) method is commonly used. In the conventional NLML method, the samples for the ML estimation of the unknown true pixel are chosen in a nonlocal fashion based on the intensity similarity of the pixel neighborhoods. Euclidean distance is generally used to measure this similarity. It has been recently shown that computing similarity measure is more robust in discrete cosine transform (DCT) subspace, compared with Euclidean image subspace. Motivated by this observation, we integrated DCT into NLML to produce an improved MRI filtration process. Other than improving the SNR, the time complexity of the conventional NLML can also be significantly reduced through the proposed approach. On synthetic MR brain image, an average improvement of 5% in PSNR and 86%reduction in execution time is achieved with a search window size of 91 × 91 after incorporating the improvements in the existing NLML method. On an experimental kiwi fruit image an improvement of 10% in PSNR is achieved. We did experiments on both simulated and real data sets to validate and to demonstrate the effectiveness of the proposed method. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 256–264, 2015     

An Enhanced Jacobi Precoder for Downlink Massive MIMO Systems

Linear precoding methods such as zero-forcing (ZF) are near optimal for downlink massive multi-user multiple input multiple output (MIMO) systems due to their asymptotic channel property. However, as the number of users increases, the computational complexity of obtaining the inverse matrix of the gram matrix increases. For solving the computational complexity problem, this paper proposes an improved Jacobi (JC)-based precoder to improve error performance of the conventional JC in the downlink massive MIMO systems. The conventional JC was studied for solving the high computational complexity of the ZF algorithm and was able to achieve parallel implementation. However, the conventional JC has poor error performance when the number of users increases, which means that the diagonal dominance component of the gram matrix is reduced. In this paper, the preconditioning method is proposed to improve the error performance. Before executing the JC, the condition number of the linear equation and spectrum radius of the iteration matrix are reduced by multiplying the preconditioning matrix of the linear equation. To further reduce the condition number of the linear equation, this paper proposes a polynomial expansion precondition matrix that supplements diagonal components. The results show that the proposed method provides better performance than other iterative methods and has similar performance to the ZF.     

基于圆柱衍射与离散余弦变换的图像光学加密算法

目的为了实现多幅图像的同步加密,并增强加密系统的抗破译能力,提出一种基于圆柱衍射域的相位截断与离散余弦变换的多图像光学加密算法。方法首先引入压缩感知(CS,Compress Transform)方法,对输入明文实施压缩;基于离散余弦变换DCT(Discrete Cosine Transform)对压缩明文完成分解,获取相应的DCT系数,形成系数矩阵;构建迭代复数,将每个压缩明文对应的系数矩阵融合为一个复矩阵,通过DCT逆变换,形成一幅组合图像。联合Hilbert变换与波带片相位模型,构建调制掩码;引入圆柱衍射域的相位截断机制,联合调制掩码,对组合图像实施光学加密,获取密文与私钥。结果实验数据表明,相对于已有的多图像同步加密方法而言,所提算法具备更高的加密安全性,密文熵值以及相邻像素间的相关系数分别达到了7.998,0.0012,且具有强烈的密钥敏感性。结论所提加密算法可以抵御网络中外来攻击,在图像信息防伪领域具有一定的参考价值。     

Parallel implementation of spectral element method for Lamb wave propagation modeling

The proposed spectral element method implementation is based on sparse matrix storage of local shape function derivatives calculated at Gauss–Lobatto–Legendre points. The algorithm utilizes two basic operations: multiplication of sparse matrix by vector and element‐by‐element vectors multiplication. Compute‐intensive operations are performed for a part of equation of motion derived at the degree of freedom level of 3D isoparametric spectral elements. The assembly is performed at the force vector in such a way that atomic operations are minimized. This is achieved by a new mesh coloring technique The proposed parallel implementation of spectral element method on GPU is applied for the first time for Lamb wave simulations. It has been found that computation on multicore GPU is up to 14 times faster than on single CPU. Copyright © 2015 John Wiley & Sons, Ltd.     

基于卷积神经网络与门控循环单元的气液两相流流型识别方法

提出了一种基于卷积神经网络(CNN)与门控循环单元(GRU)的垂直管道气液两相流流型识别方法。该方法基于电阻层析成像(ERT)系统的重建图像,对其填充处理后进行离散余弦变换(DCT),求取最大、最小 DCT 系数的差值,选取一定帧数长度数据作为网络输入,对流型进行识别。分析了输入序列长度对CNN-GRU、CNN 及 GRU 网络分类准确的影响,确定了最佳输入向量维度分别为 60、65 及 50,使用实验数据对3种网络进行训练、测试,结果表明,CNN-GRU网络分类准确率最高,平均流型识别准确率可达 99.40%。     

An efficient sparse matrix‐vector multiplication on CUDA‐enabled graphic processing units for finite element method simulations

Finite element method (FEM) is a well‐developed method to solve real‐world problems that can be modeled with differential equations. As the available computational power increases, complex and large‐size problems can be solved using FEM, which typically involves multiple degrees of freedom (DOF) per node, high order of elements, and an iterative solver requiring several sparse matrix‐vector multiplication operations. In this work, a new storage scheme is proposed for sparse matrices arising from FEM simulations with multiple DOF per node. A sparse matrix‐vector multiplication kernel and its variants using the proposed scheme are also given for CUDA‐enabled GPUs. The proposed scheme and the kernels rely on the mesh connectivity data from FEM discretization and the number of DOF per node. The proposed kernel performance was evaluated on seven test matrices for double‐precision floating point operations. The performance analysis showed that the proposed GPU kernel outperforms the ELLPACK (ELL) and CUSPARSE Hybrid (HYB) format GPU kernels by an average of 42% and 32%, respectively, on a Tesla K20c card. Copyright © 2016 John Wiley & Sons, Ltd.     

Real-time digital optical matrix multiplication with a joint-transform correlator

Joint-transform correlation architecture is employed for digital matrix multiplication. Real-valued matrix-vector, complex-valued matrix-vector, real-valued matrix-matrix, and complex-valued matrix-matrix multiplication operations can all be realized simply by programming of the data arrangement in the input plane of a multiple-input joint-transform correlator. The proposed method benefits from the advantages of speed because of the real-time processing capability of the joint-transform correlator and of high accuracy because of the digital representation of the multiplied numbers. Computer-simulation results are provided in which the negative binary encoding method is used to encode matrix elements.     

Steganalysis of images based on spatial domain and two-dimensional JPEG array

The aim of digital image steganalysis is to detect hidden information (which can be a message or an image) in a steganographic image. An ideal steganography method encrypts the information in the image such that it cannot be easily detected. Currently, a wide variety of different steganography techniques are being used; therefore, more advanced steganalysis methods are needed that can detect the steganographic images coded by different techniques. A typical steganalysis technique consists of two parts: (1) feature extraction and (2) classification. In this paper, a new steganalysis technique based on the Markov chain process is proposed. In the proposed technique, after extraction of the new features, a non-linear classifier named support vector machine is applied to classify clean and encrypted images. Analysis of variance is used to reduce the dimensions of the proposed features. The performance of the proposed technique is compared against subtractive DCT coefficient adjacency matrix (SDAM) and subtractive pixel adjacency matrix (SPAM) methods using an image database prepared by three strong steganography techniques called yet another steganographic scheme, model based, and perturbed quantization. The obtained results show that the proposed method provides better performance than SDAM and SPAM methods.     

Optical watermark scheme based on singular value decomposition ghost imaging and particle swarm optimization algorithm

An optical image watermarking algorithm, based on singular value decomposition (SVD) ghost imaging and multiple transforms, is designed. The watermark image is first encrypted by applying an SVD ghost imaging system, then the encrypted watermark is embedded into the cover image with the help of multiple transforms, including lifting wavelet transform (LWT), discrete cosine transform (DCT), discrete fractional angular transform (DFAT) and SVD. Four sub-band images are produced from the host image by LWT and DCT. The improved DFAT, whose scaling factors and parameter are optimized by particle swarm optimization algorithm, is operated in the new matrix. Afterwards, SVD is executed in the two-part image and the encrypted watermark is embedded in the host image by mutual operation of different matrices. Simulation results validate that the proposed watermark scheme is superior in the aspects of security, robustness and imperceptibility.     

Designs of optoelectronic trinary signed-digit multiplication by use of joint spatial encodings and optical correlation

Trinary signed-digit (TSD) symbolic-substitution-based (SS-based) optical adders, which were recently proposed, are used as the basic modules for designing highly parallel optical multiplications by use of cascaded optical correlators. The proposed multiplications perform carry-free generation of the multiplication partial products of two words in constant time. Also, three different multiplication designs are presented, and new joint spatial encodings for the TSD numbers are introduced. The proposed joint spatial encodings allow one to reduce the SS computation rules involved in optical multiplication. In addition, the proposed joint spatial encodings increase the space-bandwidth product of the spatial light modulators of the optical system. This increase is achieved by reduction of the numbers of pixels in the joint spatial encodings for the input TSD operands as well as reduction of the number of pixels used in the proposed matched spatial filters for the optical multipliers.     

一种安全的抗JPEG压缩半脆弱自恢复水印算法

提出一种安全的抗JPEG压缩半脆弱自恢复水印算法.该算法能有效区分JPEG压缩与恶意篡改操作,并能根据检测结果恢复篡改区域.首先,图像划分为8×8图像块,然后进行DCT变换,并量化编码为1 2位水印信息,然后生成的水印位根据随机位置序列嵌入到对应图像块的中频系数中.实验结果证明,提出的算法能有效定位篡改区域,并进行恢复...