nils-herrmann/clean_scirepeval huggingface dataset:
Temporally-Adaptive MAP Estimation for Video Denoising in the Wavelet Domain

In this paper, we propose a novel, temporally-adaptive maximum a posteriori (MAP) estimation algorithm for the reduction of additive video noise in the wavelet domain. We have exploited the fact that the spatial and temporal redundancies, which exist in a video sequence in the time domain, also persist in the wavelet domain. This allows the video motion to be captured in the wavelet domain. A new statistical model for video sequences is proposed, where the subband coefficients in individual frames as well as the wavelet coefficient difference occurring between two consecutive frames are modeled using the generalized Laplacian distribution. Based on this model, a MAP estimator is developed that estimates the noise-free wavelet coefficients in the current frame, conditioned on the noisy coefficients in the current frame and the filtered coefficients in the past frame. The proposed algorithm has been tested using several different test sequences and corrupting noise powers and the experimental results show that the proposed scheme outperforms several state-of-the-art spatio-temporal filters in time and wavelet domains in terms of quantitative performance as well as visual quality.
A Method for Automatic Segmentation of Nuclei in Phase-Contrast Images Based on Intensity, Convexity and Texture

This paper presents a method for automatic segmentation of nuclei in phase-contrast images using the intensity, convexity and texture of the nuclei. The proposed method consists of three main stages: preprocessing, h-maxima transformation-based marker controlled watershed segmentation ( h-TMC), and texture analysis. In the preprocessing stage, a top-hat filter is used to increase the contrast and suppress the non-uniform illumination, shading, and other imaging artifacts in the input image. The nuclei segmentation stage consists of a distance transformation, h-maxima transformation and watershed segmentation. These transformations utilize the intensity information and the convexity property of the nucleus for the purpose of detecting a single marker in every nucleus; these markers are then used in the h-TMC watershed algorithm to obtain segments of the nuclei. However, dust particles, imaging artifacts, or prolonged cell cytoplasm may falsely be segmented as nuclei at this stage, and thus may lead to an inaccurate analysis of the cell image. In order to identify and remove these non-nuclei segments, in the third stage a texture analysis is performed, that uses six of the Haralick measures along with the AdaBoost algorithm. The novelty of the proposed method is that it introduces a systematic framework that utilizes intensity, convexity, and texture information to achieve a high accuracy for automatic segmentation of nuclei in the phase-contrast images. Extensive experiments are performed demonstrating the superior performance ( precision = 0.948; recall = 0.924; F1-measure = 0.936; validation based on ~ 4850 manually-labeled nuclei) of the proposed method.
Design of a multidimensional split vector-radix decimation-in-frequency FFT algorithm

In this paper, the existing one-dimensional (1-D) radix-2/4 decimation-in-frequency (DIF) fast Fourier transform (FFT) algorithm is generalized to the case of an arbitrary dimension by introducing a mixture of radix-(2 times 2 times ... times 2) and radix-(4 times 4 times ... times 4) index maps. The introduction of these index maps coupled with an appropriate use of the Kronecker product enable us to design an efficient multi-dimensional (M-D) split vector-radix DIF FFT algorithm and characterize its butterfly by simple closed-form expressions allowing easy software or hardware implementation of the algorithm for any dimension. It is shown that the proposed algorithm substantially reduces the complexity compared to the existing M-D FFT
FPGA Based Reconfigurable 200 MHz Transmitter and Receiver Front End for MIMO-OFDM

This paper focuses on design, implementation and optimization of digital front end module of Multiple Input Multiple Output (MIMO)-Orthogonal Frequency Division Multiplexing (OFDM) system on FPGA employing Alamouti Technique (Space Time Block coding). MIMO-OFDM can very effectively be used to achieve higher data rates and higher reliability and this is going to be the Key for 4G Technology. MIMO-OFDM designed in this work consists of Input/Output memory, 16-QAM modulator, MIMO Encoder( Space Time Encoder), Wireless Channel Model, MIMO Decoder( Space Time Decoder) and 16-QAM Demodulator. This paper has resulted in the development of a hardware prototype of a MIMO Transmitter, Receiver and channel, which works at the speed of 200MHz on a Spartan-3 FPGA board. Test benches for individual model were developed and tested it for its correct functionality. The functional simulation was carried out for the entire design. The entire design was mapped on to FPGA.
A lattice structure for linear-phase perfect reconstruction filter banks with mirror image symmetric frequency response

In this paper, the lattice structure of a class of filter banks that possesses both the linear-phase property and the mirror-image symmetry, referred to as MIS-LPPRFB, has been investigated. By combining the MIS and the LP constraints and proposing a new simplified scheme, a reduced lattice structure with fewer parameters has been developed. It is shown that the introduction of the MIS has imposed certain constraints on the invertible matrices in the lattice structure of the conventional LPPRFBs, reducing the number of free parameters by nearly one-half Using the new lattice structure, the optimization design problem of MIS-LPPRFBs is also addressed with an objective of achieving a high performance filter bank for its use in image compression coding.
Modeling of the DCT coefficients of images

In this paper, the symmetric normal inverse Gaussian (SNIG) probability density function (PDF) is proposed as a highly suitable prior for modelling the DCT coefficients of natural images. A new method, based on minimizing the Kullback-Leibler divergence between the proposed prior and the empirical PDF extracted from image data, is proposed to estimate the SNIG parameters. The efficacy of the proposed parameter estimation technique is tested using Monte-Carlo simulations. It is shown that the SNIG PDF is a more effective prior as compared to the generalized Gaussian (GG), alpha-stable, and Laplacian PDFs for modelling the full-frame DCT coefficients of natural images. For the block-DCT coefficients, the SNIG PDF is shown to be better than the GG and Laplacian PDFs, and comparable to the instable one, while incurring much less complexity for parameter estimation.
Boiler plant control using a minimum order dynamic pole placement compensator

A quadratic performance index with a prescribed degree of stability is used to select the desired closed loop poles of a boiler plant in a 150 MW power station. Using only the available output variables for feedback. Fortran computer programs are written to design a dynamic compensator of minimum order p to achieve placement of the desired closed loop poles. The plant and the dynamic output feedback controller are simulated on a CDC Cyber 170-835 digital computer. The performance of the boiler plant controlled by the dynamic compensator is compared to performances under observer-based and state feedback controllers.
Wavelet-Based Despeckling of Medical Ultrasound Images with the Symmetric Normal Inverse Gaussian Prior

A major problem in medical ultrasonography is the inherent corruption of ultrasound images with speckle noise that severely hampers the diagnosis and automatic image processing tasks. In this paper, an efficient wavelet-based method is proposed for despeckling medical ultrasound images. A closed-form Bayesian wavelet-based maximum a posteriori denoiser is developed in a homomorphic framework, based on modelling the wavelet coefficients of the log-transform of the reflectivity with a symmetric normal inverse Gaussian (SNIG) prior. A simple method is presented for obtaining the parameters of the SNIG prior using local neighbors. Thus, the proposed method is spatially adaptive. Experiments are carried out using synthetically speckled and real ultrasound images, and the results show that the proposed method performs better than several other existing methods in terms of the signal-to-noise ratio and visual quality.
Derivative of phase spectrum of truncated autoregressive signals

Truncation of an autoregressive (AR) signal in time-domain results in spectral leakage in the frequency domain and hence, the magnitude and phase spectra and the derivative of phase spectrum (DPS) are distorted. In this paper, we show that the DPS is the least affected one when a signal is truncated. In view of the fact that several important features of a signal are preserved in its phase and DPS, this result is expected to find useful applications.
Optimal power allocation for massive MU-MIMO downlink TDD systems

This paper considers a massive multi-user MIMO downlink time-division duplex system where a large number of antennas at the base station serves single-antenna users in the same time-frequency resource. In the downlink channel, we assume that users obtain an efficient information on the channel state, with the aid of pilot sequences transmitted by BS, to decode the data signals. It is assumed that there is a channel reciprocity between the downlink channel and uplink channel in time-division duplex mode. In this case, users first transmit a pilot sequence to BS, then BS estimates the CSI and precede beamforming training sequences for users. Each user uses minimum mean-square error channel estimation to obtain the estimation of the effective channel gains. Then, users receive the data signal from BS in the rest of the channel coherence time. A lower bound on the capacity is derived in the downlink channel to evaluate the spectral efficiency when BS employs maximum ratio transmission precoding. We also propose a new method of power allocation among the pilot sequences and data signals during a length of coherence time of channel in order to maximize the spectral efficiency for a given total energy budget. The benefits of the optimal power allocation method is verified by the results obtained through simulation. It is shown that more data signal power should be used at high signal-to-noise ratios.
A vector based fast block motion estimation algorithm for implementation on SIMD architectures

In this paper, a fast block motion estimation algorithm that not only accelerates the process of the motion estimation but also maintains the same accuracy as that of the full search algorithm is proposed. In modern CPUs, the single instruction multiple data (SIMD) technique is commonly used to provide an execution speedup of up to eight fold. The proposed algorithm satisfies the requirements of (i) the easy computation of the lower bounds of the block matching error, and (ii) their storage in a contiguous memory space for its SIMD implementation. Simulation results show that the proposed algorithm is more than 40 times faster than the full search algorithm while keeping the accuracy of the latter.
A New Precision Voltage Control Scheme for the Amplitude of Oscillators

A simple technique for precisely controlling the amplitude of oscillators is described. The control parameter is a voltage and the relationship between this voltage and the amplitude of oscillation is linear. Two applications of the scheme, namely, in amplitude stabilization of oscillators and in generation of stabilized amplitude modulated signals, are discussed. Experimental results agree closely with the expected performances. The scheme is versatile and suitable for mass production.
Semiblind Sparse Channel Estimation for MIMO-OFDM Systems

In this paper, a semiblind algorithm is presented for the estimation of sparse multiple-input-multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) channels. An analysis of the second-order statistics of the signal that was received through a sparse MIMO channel is first conducted, showing that the correlation matrices of the received signal can be expressed in terms of the most significant taps (MSTs) of the sparse channel. This relationship is used to derive a blind constraint for the effective channel vector that corresponds to the MST position. The blind constraint is then combined with the training-based least square criterion to develop a semiblind approach for the estimation of MSTs of the sparse channel. A signal perturbation analysis of the proposed approach is conducted, showing that the new semiblind solution is not subject to the signal perturbation error when the sparse channel is a decimated version of a full finite impulse response channel. Furthermore, the proposed sparse semiblind algorithm has been extended for the estimation of channels in the upsampling domain for MIMO-OFDM systems with pulse shaping. A number of computer-simulation-based experiments for various sparse channels are carried out to confirm the effectiveness of the proposed semiblind approach.
Online multi-person tracking via robust collaborative model

The past decade has witnessed significant progress in object detection and tracking in videos. In this paper, we present a model for collaboration between a pre-trained object detector and multiple single object trackers in the particle filter tracking framework. For each frame, we construct an association between the trackers and the detections, and when a tracker is successfully associated to a detection, we treat this detection as the key-sample for this tracker. We present a dual motion model that incorporates the associated detections with the object dynamics. Then, a likelihood function provides different weights for the propagated and the newly created particles, reducing the effect of false positives and missed detections in the tracking process. In addition, we use generative and discriminative appearance models to maximize the appearance variation among the targets. The performance of the proposed algorithm compares favorably with that of the state-of-the-art approaches on three public sequences.
Blind deconvolution of linear systems driven by non-stationary source based on almost-symmetrical time-varying ARMA model

Two blind convolution schemes based on an almost-symmetrical time-varying autoregressive moving average (ARMA) model are proposed. Such a model is constructed for analytical source signals. Blind deconvolution of two categories of sources (constant-envelope and time-varying envelope) are discussed. The uniqueness of the blind deconvolution is shown to be guaranteed.<<ETX>>
Contrast-based fusion of noisy images using discrete wavelet transform

Development of efficient fusion algorithms is becoming increasingly important for obtaining a more informative image from several source images captured by different modes of imaging systems or multiple sensors. Since noise is inherent in practical imaging systems or sensors, an integrated approach of image fusion and noise reduction is essential. The discrete wavelet transform has been significantly successful in the development of fusion algorithms for noise-free images as well as in image denoising algorithms. A novel contrast-based image fusion algorithm is proposed in the wavelet domain for noisy source images. Novel features of the proposed fusion method are the noise reduction taking into consideration the linear dependency among the noisy source images and introducing an appropriate modification of the magnitude of the wavelet coefficients depending on the noise strength. Experiments are carried out on a number of commonly-used greyscale and colour test images to evaluate the performance of the proposed method. Results show that the performance of the proposed fusion method is better than that of other methods in terms of several frequently-used metrics, such as the structural similarity, peak signal-to-noise ratio and cross-entropy, as well as in the visual quality, even in the case of correlated noise.
An alternative approach to the design and synthesis of higher-order Bode-type variable-amplitude wave-digital equalizers

This paper presents an alternative approach to the design and synthesis of higher-order Bode-type variable-amplitude (VA) wave-digital (WD) equalizers. The proposed approach is based on, (a) the development of a theoretical method for the derivation of a corresponding VA analog equalizer shaping transfer function starting from a set of high-level system design specifications, (b) the development of a synthesis approach for a suitable analog prototype reference network for a WD equalizer realization requiring one single variable digital multiplier only, and (c) the development of a method for the transformation of the analog prototype reference network to the desired VA WD equalizer without making any recourse to the use of three-port series or parallel adapters inherent in the conventional WD realization techniques. The resulting VA WD equalizers permit the continuous variation of the WD equalizer transfer function from the shaping transfer function to its inverse through the use of a single variable digital multiplier. In addition, they exhibit the important practical feature that a geometrically symmetric change in the value of the variable digital multiplier causes a corresponding arithmetically symmetric change in the logarithmic magnitude-frequency response of the WD equalizer. An application example is given to illustrate the main results.
Wavelet-domain image denoising algorithm using series expansion of coefficient P.D.F. in terms of Hermite polynomials

A new wavelet-domain image denoising algorithm is proposed that uses series expansion of continuous probability density function (pdf) for estimating wavelet coefficient variance field. The expanded pdf is derived using standard normal as weighting function that results the Hermite polynomials in the series. Variance field estimated using the proposed algorithm is used in a minimum mean square error (MMSE) estimator to restore the noisy image wavelet coefficients. Simulation results on standard images show improved performance both in visual quality and in terms of peak signal to noise ratio (PSNR) as compared to other recent image denoising methods.
Arithmetic complexity of the split-radix FFT algorithms

A radix-2/16 decimation-in-frequency (DIF) fast Fourier transform (FFT) algorithm and its higher radix version, namely radix-4/16 DIF FFT algorithm, are proposed by suitably mixing the radix-2, radix-4 and radix-16 index maps, and combing some of the twiddle factors. It is shown that the proposed algorithms and the existing radix-2/4 and radix-2/8 FFT algorithms require exactly the same number of arithmetic operations (multiplications+additions). Moreover, by using techniques similar to these, it can be shown that all the possible split-radix FFT algorithms of the type radix-2/sup r//2/sup rs/ for computing a 2/sup m/-point DFT require exactly the same number of arithmetic operations.
A new open loop delayless subband adaptive filter structure

Subband techniques have been recently developed for adaptive filters, since some of the applications such as acoustic echo cancellation and wideband active noise control need adaptive filters with hundreds of taps, which result in high computational complexity and low convergence rate. By the use of subband adaptive algorithms, the computational complexity may be reduced along with convergence rate; however, a delay is introduced in the signal path. To remove the delay, the delayless subband adaptive filter architecture with both the open loop and the closed loop structures have been introduced. This paper presents a new open loop delayless subband adaptive filter structure with critical sampling, where the performance concerning the mean square error of the subband adaptive algorithm, caused due to the aliasing existing in the subband structure, is superior to the results obtained up to now for open loop delayless structures.
High Speed Modified Booth Encoder Multiplier for Signed and Unsigned Numbers

This paper presents the design and implementation of signed-unsigned Modified Booth Encoding (SUMBE) multiplier. The present Modified Booth Encoding (MBE) multiplier and the Baugh-Wooley multiplier perform multiplication operation on signed numbers only. The array multiplier and Braun array multipliers perform multiplication operation on unsigned numbers only. Thus, the requirement of the modern computer system is a dedicated and very high speed unique multiplier unit for signed and unsigned numbers. Therefore, this paper presents the design and implementation of SUMBE multiplier. The modified Booth Encoder circuit generates half the partial products in parallel. By extending sign bit of the operands and generating an additional partial product the SUMBE multiplier is obtained. The Carry Save Adderr (CSA) tree and the final Carry Look ahead (CLA) adder used to speed up the multiplier operation. Since signed and unsigned multiplication operation is performed by the same multiplier unit the required hardware and the chip area reduces and this in turn reduces power dissipation and cost of a system.
A novel approach to the exact design of first- and second-order Bode-type variable-amplitude bilinear-LDI switched-capacitor equalizers

This paper presents a novel approach to the exact design of first- and second-order Bode-type variable-amplitude (VA) bilinear-LDI switched-capacitor (SC) equalizers. The proposed design approach is based on the realization of the VA equalizer transfer function as the transfer function of a frequency-independent two-terminal-pair SC network at its input terminal-pair when its output terminal-pair is terminated in a (frequency-dependent) SC one-terminal-pair realization of the dual of the equalizer shaping impedance function. The resulting first-order equalizers produce fan-shaped lowpass or highpass magnitude-frequency responses, while the resulting second-order equalizer produces a bump-shaped (bandpass) magnitude-frequency response. The salient feature of the proposed SC equalizers is that only a single variable capacitor is required to control the fan amplitude in the first-order equalizers and the bump amplitude in the second-order equalizer. Moreover, these equalizers remain BIBO stable for all possible values of the variable capacitor. In addition, they exhibit the important practical feature that a geometrically symmetric change in the value of the variable capacitor causes a corresponding arithmetically symmetric change in the logarithmic magnitude-frequency response of the VA equalizer. An application example is given to illustrate the main results.
Visual tracking via bilateral 2DPCA and robust coding

The success of sparse representation, in face recognition and visual tracking, has attracted much attention in computer vision in spite of its computational complexity. However, these sparse representation-based methods often assume that the coding residual follows either Gaussian or Laplacian distribution, which may not be precise enough to describe the coding residuals in real tracking situations. With the aim of dealing such coding residuals, in this paper, a novel generative tracker is proposed in a Bayesian inference framework by exploiting both the bilateral 2D principle component analysis (B2DPCA) and robust coding. As the coding residual is two-dimensional, the weighted residual minimization is extended and is introduced into B2DPCA reconstruction without considering the much complex ℓ1-regularization. Further, it is to proposed use the weights obtained during the process of residual minimization for generating an occlusion matrix, which is used to enhance the tracker updates. The proposed method is evaluated on the challenging image sequences available in the literature, and it is demonstrated that the proposed method performs favorably when compared with the several state-of-the-art methods.