M. Omair Ahmad

A constrained anti-Hebbian learning algorithm for total least-squares estimation with applications to adaptive FIR and IIR filtering

In this paper, a new Hebbian-type learning algorithm for the total least-squares parameter estimation is presented. The algorithm is derived from the classical Hebbian rule. An asymptotic analysis is carried out to show that the algorithm allows the weight vector of a linear neuron unit to converge to the eigenvector associated with the smallest eigenvalue of the correlation matrix of the input signal. When the algorithm is applied to solve parameter estimation problems, the converged weights directly yield the total least-squares solution. Since the process of obtaining the estimate is optimal in the total least-squares sense, its noise rejection capability is superior to those of the least-squares-based algorithms. It is shown that the implementations of the proposed algorithm have the simplicity of those of the LMS algorithm. The applicability and performance of the algorithm are demonstrated through computer simulations of adaptive FIR and IIR parameter estimation problems. >

Carrier Frequency Offset Estimation and I/Q Imbalance Compensation for OFDM Systems

Two types of radio-frequency front-end imperfections, that is, carrier frequency offset and the inphase/quadrature (I/Q) imbalance are considered for orthogonal frequency division multiplexing (OFDM) communication systems. A preamble-assisted carrier frequency estimator is proposed along with an I/Q imbalance compensation scheme. The new frequency estimator reveals the relationship between the inphase and the quadrature components of the received preamble and extracts the frequency offset from the phase shift caused by the frequency offset and the cross-talk interference due to the I/Q imbalance. The proposed frequency estimation algorithm is fast, efficient, and robust to I/Q imbalance. An I/Q imbalance estimation/compensation algorithm is also presented by solving a least-square problem formulated using the same preamble as employed for the frequency offset estimation. The computational complexity of the I/Q estimation scheme is further reduced by using part of the short symbols with a little sacrifice in the estimation accuracy. Computer simulation and comparison with some of the existing algorithms are conducted, showing the effectiveness of the proposed method.

A Study of Multiplicative Watermark Detection in the Contourlet Domain Using Alpha-Stable Distributions

In the past decade, several schemes for digital image watermarking have been proposed to protect the copyright of an image document or to provide proof of ownership in some identifiable fashion. This paper proposes a novel multiplicative watermarking scheme in the contourlet domain. The effectiveness of a watermark detector depends highly on the modeling of the transform-domain coefficients. In view of this, we first investigate the modeling of the contourlet coefficients by the alpha-stable distributions. It is shown that the univariate alphastable distribution fits the empirical data more accurately than the formerly used distributions, such as the generalized Gaussian and Laplacian, do. We also show that the bivariate alpha-stable distribution can capture the across scale dependencies of the contourlet coefficients. Motivated by the modeling results, a blind watermark detector in the contourlet domain is designed by using the univariate and bivariate alpha-stable distributions. It is shown that the detectors based on both of these distributions provide higher detection rates than that based on the generalized Gaussian distribution does. However, a watermark detector designed based on the alpha-stable distribution with a value of its parameter α other than 1 or 2 is computationally expensive because of the lack of a closed-form expression for the distribution in this case. Therefore, a watermark detector is designed based on the bivariate Cauchy member of the alpha-stable family for which α = 1. The resulting design yields a significantly reduced-complexity detector and provides a performance that is much superior to that of the GG detector and very close to that of the detector corresponding to the best-fit alpha-stable distribution. The robustness of the proposed bivariate Cauchy detector against various kinds of attacks, such as noise, filtering, and compression, is studied and shown to be superior to that of the generalized Gaussian detector.

A low-complexity parametric transform for image compression

In this paper, a one-parameter eight-point orthogonal transform suitable for image compression is proposed. An algorithm for its fast computation is developed and an efficient structure for a simple implementation valid for all possible values of its independent parameter is proposed. It is shown that an appropriate selection of the values of the parameter results in a number of new multiplication-free transforms having a good compromise between the computational complexity and performance. Applying the proposed transform to image compression, we show that it outperforms the existing transforms having complexities similar to that of the proposed one.

A novel transform for image compression

In this paper, we propose an orthogonal multiplication-free transform of order that is an integral power of two by an appropriate extension of the well-known fourthorder integer discrete cosine transform. Moreover, we develop an efficient algorithm for its fast computation. It is shown that the computational and structural complexities of the algorithm are similar to that of the Hadamard transform. By applying the proposed transform to image compression, we show that it outperforms the existing transforms having complexities similar to that of the proposed one.

A least-square design approach for 2D FIR filters with arbitrary frequency response

In this paper, a least-square approach for the design of two-dimensional (2D) complex finite-impulse response (FIR) filters with arbitrary frequency response is presented. By minimizing the frequency-domain error function and revealing some of the properties of the matrices associated with the design problem, a closed-form solution is obtained. The solution is presented as an expression for the impulse response corresponding to the desired frequency-response specification. Thus, the method avoids the usual time-consuming procedures of optimization or matrix inversion, and makes a very fast calculation of the filters coefficients possible, it is also shown that when this solution is used to design linear-phase filters and a class of 2D phase equalizers, some further computational savings can be achieved. The novel feature of the proposed approximation approach is that it can be used to design any kind of 2D FIR filters without employing any symmetry constraint on their frequency responses. Several design examples illustrating the efficiency of the approach are considered.

A fast 8×8 transform for image compression

In this paper, we propose an efficient 8×8 transform matrix for image compression by appropriately introducing some zeros in the 8×8 signed DCT matrix. We show that the proposed transform is orthogonal, which is a highly desirable property. In order to make this novel transform more attractive for recent real-time applications, we develop an efficient algorithm for its fast computation. By using this algorithm, the proposed transform requires only 18 additions to transform an 8-point sequence. Compared to the existing 8×8 approximated DCT matrices, it is shown that savings of 25% in the number of arithmetic operations can easily be achieved using the proposed transform operator without noticeable degradations in the reconstructed images. We also present simulation results using some standard test images to show the efficiency of the proposed transform in image compression.

Quadtree structured region-wise motion compensation for video compression

The conventional variable-size block motion compensation technique, even though superior to the fixed-size block motion-compensation technique, cannot fully utilize the motion information of a frame for its partitioning. This paper presents a quadtree structured region-wise motion-compensation technique that utilizes more effectively the motion content of a frame in terms of the shape, size, and location of the partitioned regions. The proposed technique is based on a new coding scheme of the quadtree structure, where a two-bit code is used. The partitioning of a given frame is carried out through the processes of merging and combining. The merging process partitions the frame into a number of regions by carrying out all possible 4-to-1, 3-to-1, and 2-to-1 merges along the quadtree hierarchy according to some specified criteria, while the combining process combines some of the partitioned regions that have the same motion vector into a single region. The motion vectors of the resulting partitioned regions are coded by a new coding scheme that uses the temporal correlation of the motion fields. Test results of applying the proposed method on a number of MPEG video sequences are included. These results indicate that the proposed method can provide a significantly improved rate-distortion performance.

An Analysis of the Tradeoff Between the Energy and Spectrum Efficiencies in an Uplink Massive MIMO-OFDM System

This brief mainly investigates energy efficiency (EE) and spectrum efficiency (SE) for the uplink massive multiple-input-multiple-output orthogonal frequency-division multiplexing system in a single-cell environment. An approximate SE expression is first derived by employing the maximum ratio combination or zero-forcing detection at the base station. Then, the theoretical tradeoff between EE and SE is established after introducing a realistic power consumption model in consideration of both the radiated power and the circuit power. Based on the tradeoff, the optimal EE with respect to SE is derived using the convex optimization theory. Results show that the optimal EE increases by deploying a suitable number of antennas, multiplexing a reasonable number of users, expanding the system bandwidth, or shrinking the cell radius. Partly different from the EE, the SE corresponding to the optimal EE can be improved by increasing the number of antennas, multiplexing a rational number of users, narrowing the system bandwidth, or shrinking the cell radius.

Video Denoising Using Motion Compensated 3-D Wavelet Transform With Integrated Recursive Temporal Filtering

A novel framework of the motion-compensated 3-D wavelet transform (MC3DWT) for video denoising is presented in this paper. The motion-compensated temporal wavelet transform is first performed on a sliding window of video frames consisting of previously denoised frames and the current noisy frame. The 2-D spatial wavelet transform is then performed on the temporal subband frames, thus realizing a 3-D wavelet transform. Any of established wavelet-based still image denoising algorithms can then be applied to the high-pass 3-D subbands. The operation of the inverse 2-D spatial wavelet transform followed by the inverse temporal wavelet transform reconstructs the video frames in the buffer. The denoised current frame may be used as an output for real-time processing; meanwhile, the past frames can be updated, one of which may be used as a delayed output for post-processing or for real-time processing that allows some amount of delay. The proposed MC3DWT framework integrates both the spatial filtering and recursive temporal filtering into the 3-D wavelet domain and effectively exploits both the spatial and temporal redundancies. Experimental results have demonstrated a superior visual and quantitative performance of the proposed scheme for various levels of noise and motion.