nils-herrmann/clean_scirepeval huggingface dataset:
Comparison of Two Frame Rate Conversion Schemes for Reducing LCD Motion Blurs

Liquid crystal display (LCD) is known to have motion blur due to the slow response and sample-hold characteristics of the liquid crystal (LC). To alleviate the LCD motion blur, improving the LC response is the most fundamental solution. However, if the response time is shortened, then more frames are needed and hence frame rate up conversion (FRUC) should be used. In this paper, we study two FRUC methods. We compare the output signal qualities by studying the temporal and spatial profile of the two methods. We use the solution of Erickson-Leslie equation to derive the step response, in contrast to the existing literature where the resistor-capacitor (RC) approximation and uniform averaging function are used. The step response we derived is able to model not only the general trend of the rising and falling edges, but also the effects of different gray level transitions. Based on the step response, we analyze the two methods by comparing the observed signal in both the spatial and temporal domain.
Reciprocal Subpixel Motion Estimation: Video Coding With Limited Hardware Resources

Conventional block-based video coding with subpixel motion compensation, requires a large pool of memory for storing up-sampled reference frames. The size of this memory for many applications, especially for encoding high definition source materials is a major design consideration. In this paper, the concept of reciprocal block matching is introduced based on the relativity of motion, especially, the translational motion. As one of the main applications for this technique, subpixel motion estimation is revisited to achieve efficient video coding when the underlying hardware only provides a small size of memory. A byproduct of the proposed algorithm is an encoding-speed boost when the encoder is to be deployed on a hardware platform with general-purpose data-caching features. This includes almost all personal computers which happen to be the main platform for desktop publishing applications. Analysis of direct (conventional) and reciprocal (proposed) subpixel motion estimation is provided to identify the sources of discrepancies between these two techniques. Finally, experimental results are provided to show the efficiency of proposed block matching scheme. All simulations are done within the frame work of reference H.264/AVC video coder
A class of regular biorthogonal linear-phase filterbanks: theory, structure, and application in image coding

This paper discusses a method of regularity imposition onto biorthogonal linear-phase M-band filterbanks using the lattice structure. A lifting structure is proposed for lattice matrix parameterization where regularity constraints can be imposed. The paper focuses on cases with analysis and synthesis filterbanks having up to two degrees of regularity. Necessary and sufficient conditions for regular filterbanks in terms of the filter impulse response, frequency response, scaling function, and wavelets are revisited and are derived in terms of the lattice matrices. This also leads to a constraint on the minimum filter length. Presented design examples are optimized for the purpose of image coding, i.e., the main objectives are coding gain and frequency selectivity. Simulation results from an image coding application also show that these transforms yield improvement in the perceptual quality in the reconstruction images. The approach has also been extended to the case of integer/rational lifting coefficients, which are desirable in many practical applications.
Multimodal sparse Bayesian dictionary learning applied to multimodal data classification

In this paper, we present a novel multimodal sparse dictionary learning algorithm based on a hierarchical sparse Bayesian framework. The framework allows for enforcing joint sparsity across dictionaries without restricting the actual entries to be equal. We show that the proposed method is able to learn dictionaries of higher quality than existing approaches. We validate our claims with extensive experiments on synthetic data as well as real-world data.
Rate Estimation, Using Forward Adaptive Quantization: H.264 Fast Intra Mode Selection at High Data Rates

This paper presents a fast method to estimate the required bits to encode a block of video data. The proposed method uses forward adaptive quantization (which uses the current sample information, not available at the decoder, to scale the sample value before and after quantization) to estimate the actual rate-distortion cost. Rate estimation has many applications in the art of video coding, where a coding decision should be made based on the optimality of a rate-distortion pair. As an example this method has been considered for fast rate-distortion optimized mode selection within H.264/AVC video coding standard. It is shown that, compared to other rate estimation methods, the proposed method more accurately predicts the optimal mode identical to the one chosen by a Lagrangian cost function based on the actual rate and distortion. The computational complexity of forward quantization is much lower than that of conventional entropy coders which makes it possible to perform the motion estimation with rate-distortion criterion as opposed to simple sum of absolute values of residual signal, which increases the efficiency of predictive coding.
Some results in the theory of crosstalk-free transmultiplexers

The crosstalk-free transmultiplexer (CF-TMUX) focuses on crosstalk cancellation (CC) rather than on suppressing it. The authors present an analysis of the CF-TMUX based on the polyphase component matrices of the filter banks used in TDM to FDM and FDM to TDM conversions, respectively. Thus a necessary and sufficient condition for complete CC is obtained. It is shown that the filters for a CF-TMUX are the same as the filters for a 1-skewed alias free QMF bank. In addition, if the QMF bank satisfies the perfect reconstruction (PR) property, then the TMUX also satisfies PR. The relation between CF-TMUX filters and alias-free QMF banks is used to obtain a direct design procedure for CF-TMUX filters (both FIR and IIR). It is also shown that approximately crosstalk-free TMUX filters can be obtained from any approximately alias-free QMC bank. Design examples and comparison tables are included.
Fast External Denoising Using Pre-Learned Transformations

We introduce a new external denoising algorithm that utilizes pre-learned transformations to accelerate filter calculations during runtime. The proposed fast external denoising (FED) algorithm shares characteristics of the powerful Targeted Image Denoising (TID) and Expected Patch Log-Likelihood (EPLL) algorithms. By moving computationally demanding steps to an offline learning stage, the proposed approach aims to find a balance between processing speed and obtaining high quality denoising estimates. We evaluate FED on three datasets with targeted databases (text, face and license plates) and also on a set of generic images without a targeted database. We show that, like TID, the proposed approach is extremely effective when the transformations are learned using a targeted database. We also demonstrate that FED converges to competitive solutions faster than EPLL and is orders of magnitude faster than TID while providing comparable denoising performance.
Analysis and Integrated Architecture Design for Overlap Smooth and in-Loop Deblocking Filter in VC-1

Unlike familiar macroblock-based in-loop deblocking filter in H.264, the filters of VC-1 perform all horizontal edges (for in-loop deblocking filtering) or vertical edges (for overlap smoothing) first and then the other directional filtering edges. The entire procedure is very time-consuming and with high memory access loading for the whole system. This paper presents a novel method and the efficient integrated architecture design, which involves an 12 times 12 overlapped block that combines overlap smoothing with loop filtering for performance and cost by sharing circuits and resources. This architecture has capability to process HDTV1080p 30 fps video and HDTV 2048 times 1536 24 fps video at 180 MHz. The same concept is applicable to other video processing algorithms, especially in deblocking filter for video post-processing in a frame-based order.
Deblocking of video sequences with lapped embedded IDCT

At mid to low bit-rates, the standard DCT based video codecs produce, in the reconstructed sequences, annoying artifacts known as ringing and blocking effects. We are concerned in blocking artifact removal with lapped embedded IDCT. In intra frames, the deblocking always produces an increase in the peak signal-to-noise ratio; as a consequence of the processing on the last reference intra frame, inter frames, whose prediction error is decoded with IDCT, are free of blocking artifacts. Using the proposed algorithm on the inter frame decreases the resulting PSNR while improving the visual quality of the decoded images. We present a theoretical bound to the PSNR reduction.
Stereo image defogging

This paper presents a new approach to estimate fog-free images from stereo foggy images. We investigate a new way to estimate transmission by computing the scattering coefficient and depth information of a scene. However, most existing visibility restoration algorithms estimate transmission independently on scattering coefficient and object distance. In the proposed method, the natural color of a foggy image is recovered using depth information from a stereo image pair even though prior knowledge or multiple images taken at different times are not required. Furthermore, we explore a new way to measure the scattering coefficient by using a stereo image pair from an image processing perspective. Experimental results verify that the proposed method outperforms the conventional defogging methods.
An OFDM-specified lossless FFT architecture

In this paper, a VLSI architecture based on radix-22 integer fast Fourier transform (IntFFT) is proposed to demonstrate its efficiency. The IntFFT algorithm guarantees the perfect reconstruction property of transformed samples. For a 64-points radix-22 FFT architecture, the proposed architecture uses 2 sets of complex multipliers (six real multipliers) and has 6 pipeline stages. By exploiting the symmetric property of lossless transform, the memory usage is reduced by 27.4%. The whole design is synthesized and simulated with a 0.18-mum TSMC 1P6M standard cell library and its reported equivalent gate count usage is 17,963 gates. The whole chip size is 975 mumtimes977 mum with a core size of 500 mumtimes500 mum. The core power consumption is 83.56 mW. A Simulink-based orthogonal frequency demodulation multiplexing platform is utilized to compare the conventional fixed-point FFT and proposed IntFFT from the viewpoint of system-level behavior in items of signal-to-quantization-noise ratio (SQNR) and bit error rate (BER). The quantization loss analysis of these two types of FFT is also derived and compared. Based on the simulation results, the proposed lossless IntFFT architecture can achieve comparative SQNR and BER performance with reduced memory usage
Analysis of motion vector errors in motion compensated frame rate up conversion

Frame rate up conversion methods that employ motion have been proven to provide better image quality compared to nonmotion based methods. While motion based methods improve the performance of interpolation; artifacts are introduced in the presence of incorrect motion vectors. In this paper, the effect of motion vector errors on the efficiency of motion compensated frame rate up conversion (MC-FRUC) and temporal interpolation filter is analyzed. The problem of MC-FRUC is investigated by combining blocks with different motion vector errors as opposed to equal error assumption. A general expression for temporal interpolation filter is derived. To improve the efficiency of the prediction, it is shown that the interpolator should be able to switch between unidirectional or bidirectional modes based on the motion vector reliability.
The morphological control of MEH-PPV films on an ITO electrode for hybrid solar cell fabrication

The poly[2-methoxy-5-(2-ethylhexyloxy-p-phenylene-vinylene)] (MEH-PPV) thin films were deposited on indium tin oxide (ITO) coated glass by using spin-coating technique at room temperature. The effect of spin-coating speed on the electrical and morphological properties of MEH-PPV film was studied. The surface roughness would be controlled by varied spin-coating speeds. I-V characteristics of ITO/MEH-PPV/Al structure have measured by solar simulator at the optimum condition.
Broadband terahertz radiation through a one-dimensional grating with a tapered slit on a high-index substrate

In this paper, we present a broadband extraordinary transmission through a one-dimensional grating at terahertz frequencies. The grating with a tapered slit is carved periodically on a high-index GaAs substrate. The material for the grating is undoped Indium Antimonide. The geometry of the tapered slit is optimized to enable the impedance matching and thus broaden the transmission at a specific incidence angle, the Brewster angle. Such grating opens several opportunities to develop ultra-thin, low-loss, and broadband terahertz metamaterial antennas and absorbers.
Data Compression using Dual Tree Complex Wavelet Transform for System Identification

Data pre-treatment is very valuable for system identification, particularly for nonlinear system modeling. This paper presents a data compression procedure using dual tree complex wavelet transform (DTCWT) for plant data pre-treatment in the context of system identification. The data is compressed to a few critical complex wavelet coefficients and denoised by the use of DTCWT. A simulation example is provided to demonstrate the performance and capabilities of the proposed approach
Comparing stress ECG enhancement algorithms

There are two predominant types of noise that contaminate the electrocardiogram (EGG) acquired during a stress test: the baseline wander noise (BW) and electrode motion artifact, and electromyogram-induced noise (EMG). BW noise is at a lower frequency, caused by respiration and motion of the subject or the leads. The frequency components of BW noise are usually below 0.5 Hz, and extend into the frequency range of the ST segment during a stress test. EMG noise, on the other hand, is predominantly at higher frequencies, caused by increased muscle activity and by mechanical forces acting on the electrodes. The frequency spectrum of the EMG noise overlaps that of the ECG signal and extends even higher in the frequency domain. In this article, the authors review some of the published ECG enhancing techniques to overcome the noise problems, and compare their performance on stress ECG signals under adverse noise scenarios. They also describe the filter bank-based ECG enhancing algorithm.
Frequency-Selective KYP Lemma, IIR Filter, and Filter Bank Design

For a transfer function F(ejomega) of order n , Kalman-Yakubovich-Popov (KYP) lemma characterizes a general intractable semi-infinite programming (SIP) condition by a tractable semidefinite programming (SDP) for the entire frequency range. Some recent results generalize this lemma for a certain frequency interval. All these SDP characterizations are given at the expense of the introduced Lyapunov matrix variable of dimension ntimesn. Consequently, formulation and design of high dimensional problem is challenging. Moreover, existing SDP characterizations for frequency-selective SIP (FS-SIP) do not allow to formulate synthesis problems as SDPs. In this paper, we propose a completely new SDP characterization of general FS-SIP involving SDPs of moderate size and free from Lyapunov variables. Furthermore, a systematic IIR filter and filter bank design is developed in a similar vein, with several simulations provided to validate the effectiveness of our SDP formulation.
Cubic Convolution Scaler Optimized for Local Property of Image Data

A scaler is one of the most important modules in various video applications, such as ultra-high definition TV and scalable video systems. A variety of scaling techniques have been used to increase the video quality when the resolution of the source image has to be up- and down-scaled. Some conventional schemes exploit the property of local block data. Others consider the edge information of the data to be scaled. In this paper, we formulate a scaling problem to minimize the information loss resulting from the resizing process. The loss is considered in both the spatial and the frequency domains, and then it is minimized to optimize the kernel of the scaler. The simulation results show that the proposed algorithm reduces the information loss more than conventional schemes. When compared with the conventional algorithms, the proposed method outperforms those with similar complexity.
Image Enhancement for Fluid Lens Camera Based on Color Correlation

The novel field of fluid lens cameras introduces unique image processing challenges. Intended for surgical applications, these fluid optics systems have a number of advantages over traditional glass lens systems. These advantages include improved miniaturization and no moving parts while zooming. However, the liquid medium creates two forms of image degradation: image distortion, which warps the image such that straight lines appear curved, and nonuniform color blur, which degrades the image such that certain color planes appear sharper than others. We propose the use of image processing techniques to reduce these degradations. To deal with image warping, we employ a conventional method that models the warping process as a degree-six polynomial in order to invert the effect. For image blur, we propose an adapted perfect reconstruction filter bank that uses high frequency sub-bands of sharp color planes to improve blurred color planes. The algorithm adjusts the number of levels in the decomposition and alters a prefilter based on crude knowledge of the blurring channel characteristics. While this paper primarily considers the use of a sharp green color plane to improve a blurred blue color plane, these methods can be applied to improve the red color plane as well, or more generally adapted to any system with high edge correlation between two images.
Optimized Analog Filter Designs With Flat Responses by Semidefinite Programming

Analog filters constitute indispensable components of analog circuits. Inspired by recent advances in digital filter design, this paper provides a flexible design for analog filters. All-pole filters have maximally flat passband, so our design minimizes their passband distortion. Analogously, maximally flat filters have maximally flat passband, so our design maximizes their stopband attenuation. Its particular cases provide flexible alternatives to the classical counterparts. Semidefinite program (SDP) formulations for the posed filter design problems are presented, which are efficiently solved by existing optimization software. Several examples and comparisons are provided to validate the viability of our design.
Critical quantization decisions in transform coding and blocking artifacts

In this work, a mechanism contributing to the blocking artifacts of standard block based transform coding schemes is stated and a simple solution is proposed for reducing its effect. The proposed solution can be easily incorporated into the encoding algorithms of existing two dimensional (2-D) discrete cosine transform (DCT) based image and video coding standards (JPEG, MPEG-1 and 2, H-261, H-263) without the need for a modification in their bitstream syntax.
Color Image Superresolution Based on a Stochastic Combinational Classification-Regression Algorithm

The proposed algorithm in this work provides superresolution for color images by using a learning based technique that utilizes both generative and discriminant approaches. The combination of the two approaches is designed with a stochastic classification-regression framework where a color image patch is first classified by its content, and then, based on the class of the patch, a learned regression provides the optimal solution. For good generalization, the classification portion of the algorithm determines the probability that the image patch is in a given class by modeling all possible image content (learned through a training set) as a Gaussian mixture, with each Gaussian of the mixture portraying a single class. The regression portion of the algorithm has been chosen to be a modified Support Vector Regression, where the kernel has been learned by solving a semi definite programming (SDP) and quadratically constrained quadratic programming (QCQP) problem. The SVR is further modified by scaling the training points in the SDP and QCQP problems by their relevance and importance to the examined regression. The result is a weighted average of different regressions depending on how much a single regression is likely to contribute, where advantages include reduced problem complexity, specificity with regard to image content, added degrees of freedom from a nonlinear approaches, and excellent generalization that a combined methodology has over its individual counterparts.
Discontinuity-Adaptive De-Interlacing Scheme Using Markov Random Field Model

In this paper, a de-interlacing algorithm to find the optimal deinterlaced results given accuracy-limited motion information is proposed. The de-interlacing process is formulated as a maximum a posteriori (MAP)-Markov random field (MRF) problem. The MAP solution is the one that minimizes an energy function. The energy function imposes discontinuity adaptive smoothness constraint upon the deinterlaced frame. Simulation results show that the MAP-MRF formulation is efficient and the high frequency noise is removed in a few iterations.
Hardware-in-the-Loop approach to controller design and testing of motion control systems using xPC Target

Hardware-in-the-Loop (HiL) has been a proven technique, widely used in the development and testing of real-time embedded systems, especially in the automotive industry. This paper describes the development of a HiL simulation platform for motion control systems, demonstrated with an example of Permanent Magnet Synchronous Motor (PMSM) control system development and testing. The platform uses industry graded hardware, i.e. Mitsubishi IGBT driver, high performance SEM PMSM motor, etc. as well as various measurement sensors and associated electronics. Here, the platform main computational core is implemented using xPC Target platform which enables rapid validation, prototyping and deployment of tested control modules via Matlab and Simulink.
A novel combination of negative and positive selection in Artificial Immune Systems

Artificial Immune System (AIS) is a multidisciplinary research area that combines the principles of immunology and computation. Negative Selection Algorithms (NSA) is one of the most popular models of AIS mainly designed for one-class learning problems such as anomaly detection . Positive Selection Algorithms (PSA) is the twin brother of NSA with similar performance for AIS . Both NSAs and PSAs comprise of two phases: generating a set D of detectors from a given set S of selves (detector generation phase); and then detecting if a given cell (new data instance) is self or non-self using the generated detector set (detection phase). In this paper, we propose a novel approach to combining NSAs and PSAs that employ binary representation and r-chunk matching rule. The new algorithm achieves smaller detector storage complexity and potentially better detection time in comparison with single NSAs or PSAs.