nils-herrmann/clean_scirepeval huggingface dataset:
Modifications to the Liang, McClellan and Parks computer program for designing optimal recursive multirate digital filters

A class of recursive digital filters of the form H(z)=A(z)/B(z/sup D/) for sampling rate conversion is designed with an iterative Remez exchange algorithm. Simple modifications are made to the Liang, McClellan, and Parks computer program for designing these multirate digital filters. The resulting filters can greatly reduce the multiplication rate and the coefficients memory storage. Some design examples are presented to show the effectiveness of this approach.
Two dimensional nonuniform perfect reconstruction filter bank with irrational down-sampling matrices

In this paper, we propose a new method to realize an irrational scaling of a 2D digital signal/image. This method is suitable for any scaling matrices with real entries, including irrational numbers. Based on this algorithm, a new structure of a 2D four-channel non-uniform perfect reconstruction filter bank is derived. Through the proposed structure, it is now possible to segment the 2D frequency components of a 2D digital signal/image arbitrarily through a careful design of the scaling matrix while still preserving the PR property. Therefore, we can find many applications such as image compression and communication using this structure. The experimental results are presented at the end of this paper.
Extracting color features and dynamic matching for image database retrieval

Color-based indexing is an important tool in image database retrieval. Compared with other features of the image, color features are less sensitive to noise and background complication. Based on the human visual system's perception of color information, this paper presents a dependent scalar quantization approach to extract the characteristic colors of an image as color features. The characteristic colors are suitably arranged in order to obtain a sequence of feature vectors. Using this sequence of feature vectors, a dynamic matching method is then employed to match the query image with database images for a nonstationary identification environment. The empirical results show that the characteristic colors are reliable color features for image database retrieval. In addition, the proposed matching method has acceptable accuracy of image retrieval compared with existing methods.
The Multiple-Parameter Discrete Fractional Fourier Transform and Its Application

The discrete fractional Fourier transform (DFRFT) is a generalization of the discrete Fourier transform (DFT) with one additional order parameter. In this paper, we extend the DFRFT to have N order parameters, where N is the number of the input data points. The proposed multiple-parameter discrete fractional Fourier transform (MPDFRFT) is shown to have all of the desired properties for fractional transforms. In fact, the MPDFRFT reduces to the DFRFT when all of its order parameters are the same. To show an application example of the MPDFRFT, we exploit its multiple-parameter feature and propose the double random phase encoding in the MPDFRFT domain for encrypting digital data. The proposed encoding scheme in the MPDFRFT domain significantly enhances data security
Dilated and Shifted Discrete Hermite Functions With Minimum Time-Bandwidth Product

In this letter, a novel method is proposed to generate discrete approximations of continuous Hermite–Gaussian functions with noninteger shift and dilation. Moreover, the approximations preserve orthogonality. In addition, the discrete Hermite–Gaussian functions reach the minimum time-bandwidth product under discrete version of Gabor uncertainty principle. Two applications are demonstrated. In fractional delay application, the proposed method is compared with the windowing method and proved to have smaller delay error. Another one is the signal expansion based on the proposed complete orthogonal basis.
Global motion estimation in model-based image coding by tracking three-dimensional contour feature points

A video coding method called model-based image coding has attracted much attention as a potential candidate for low bit-rate visual communication services. This technique reconstructs the facial image with a preknown 3D human face model and its received model motion parameters. The parameters of the head motion are mainly divided into two parts: global motion parameters describe the rigid movement of the head, such as rotation and translation, and local motion parameters which deal with the nonrigid movements of facial expressions, such as the opening and closing of the mouth and eyes. In this paper, we propose a new approach which can estimate the head global motion more robustly and accurately. Comparing with the existing techniques to match only a few key points, here we extract 3-D contour feature points and use chamfer distance matching to estimate head global motion. This can improve and enhance the contour tracking performance greatly. We also develop another technique called facial normalization transform. It maps the facial region of the current input frame back to the normalized pose of the initial frame. Using this transform, we can analyze facial expressions at the same orientation and fixed region. This simplifies the analysis work a lot. Then, we do our encoding by the clip-and-paste method along with adaptive codebook technique. In the following the coder and decoder system are briefly described.
A Novel Image Recovery Algorithm for Visible Watermarked Images

A novel image recovery algorithm for removing visible watermarks is presented. Independent component analysis (ICA) is utilized to separate source images from watermarked and reference images. Three independent component analysis approaches are examined in the proposed algorithm, which includes joint approximate diagonalization of eigenmatrices, second-order blind identification, and FastICA. Moreover, five different visible watermarking methods to embed uniform and linear-gradient watermarks are implemented. The experimental results show that visible watermarks are successfully removed, and that the proposed algorithm is independent of both the adopted ICA approach and the visible watermarking method. In the final experiment, several public domain images sourced from various websites are tested. The results of this study demonstrate that the proposed algorithm can blindly and successfully remove the visible watermarks without knowing the watermarking methods in advance
WLS Design of Variable Fractional-Delay FIR Filters Using Coefficient Relationship

In this brief, a new coefficient relationship is proposed for the design of variable fractional-delay (VFD) finite-impulse response (FIR) filters by the weighted least-squares (WLS) method so that the number of filter coefficients to be designed can approximately be halved. To reduce the computational cost, closed-form expressions for the elements of related vectors and matrices are derived. Several design examples are presented, and the comparisons show that the overall performance of the proposed method is comparable with that of the conventional method; however, the number of filter coefficients to be designed for the proposed method is about half of that in the conventional method.
Fast design of 2-D linear-phase complex FIR digital filters by analytical least squares method

Two-dimensional full-plane and half-plane filters are more general, and much better frequency responses can be obtained than the quarter-plane filters. In this correspondence, the analytical least squares method is generalized and extended for designing 2-D full-plane and half-plane linear phase complex FIR digital filters. The 2-D filter's coefficients can be effectively determined by use of a closed-form transformation matrix and some simple element functions. The unique advantage of this technique is that it is very fast without employing iterative optimization procedures and matrix inversions. Design examples are presented to illustrate the simplicity and efficiency of the proposed method.
Two dimensional IIR and FIR digital notch filter design

The two-dimensional 2-D digital notch filter design problem is investigated. A simple algebraic method for 2-D infinite impulse response (IIR) notch filter design is developed. This approach not only has closed-form transfer function, but also satisfies the bounded input bounded output (BIBO) stability condition. The Lagrange multiplier method is used to design 2-D finite impulse response (FIR) notch filters. This design is optimal in least square sense. The 2-D notch filter is applied to eliminate sinusoidal or narrowband interferences superimposed on an image. Simulation results are presented to demonstrate the effectiveness of these approaches.<<ETX>>
Efficient design of 2D multiplierless FIR filters by transformation

This paper deals with the design of 2D multiplierless FIR digital filters, first a special class of multiplierless 1D FIR filters are designed with coefficients which are a sum or difference of power-of-two, and then map it into 2D multiplierless FIR filters by McClellan transform; This technique has the advantage that it is very fast, because only a 1-D filter must be designed, also the hardware implementation for these 2D FIR filters is very attractive and efficient.
On optimal low-rank approximation of multidimensional discrete signals

This brief describes an algorithmic development of the optimal low-rank approximation (LRA) of multidimensional (M-D) signals with M/spl ges/3. The algorithms developed can be regarded as a dimensional generalization of the singular value decomposition (SVD) which is of fundamental importance for analyzing signals that can be represented in a matrix form. In particular, iterative algorithms for optimal and suboptimal LRA of three-dimensional (3-D) arrays are presented in detail. Application of the 3-D LRA to the compression of image sequences is discussed.
Design of IIR fractional differentiator With Peano kernel

A discrete fractional differentiator is proposed in this paper. Through a time domain analysis of the ideal input and output signal of a LTI system, we derive a set of linear equations which can be solved numerically for the filterpsilas impulse response. We also show that the difference between the designed system and the ideal system can be represented by the Peano kernel of the system. Some designing examples of the proposed filter are also demonstrated.
FIR filter design based on total least squares error criterion

In this paper, an FIR filter design based on total least squares error criterion is investigated. The filter coefficients are obtained from the elements of the eigenvector corresponding to minimum eigenvalue of a real, symmetric and positive definite matrix. This design is not only optimal in total least squares error sense, it is also easy to incorporate linear constraints in time and frequency domain. Several design examples are used to illustrate the effectiveness of this new design approach.
Effective color interpolation in CCD color filter array using signal correlation

We propose an effective color filter array interpolation method for digital still cameras using a simple image model that correlates the R, G, B channels. The main contribution of this paper is that we propose a low complexity interpolation method to improve the image quality. Simulation results verify that the proposed method obtain superior image quality. The G channel of the proposed method outperforms the bilinear method by 6.34 dB, and the R, B channels have a 7.69 dB improvement in average. Furthermore, the complexity of the proposed method is acceptable compared with the existing methods.
Generally Dimensional and Constellation Expansion Free Space–Time Block Codes for QAM With Full Diversity

This correspondence presents new rate-1 space-time block codes (STBCs) attending full diversity over every quadrature amplitude modulation (QAM) constellation when the number of Tx antennas is a power of two. From the simulation results, our design performs very closely to the quasi-orthogonal code with constellation rotation over 4-QAM and 16-QAM in the case of four Tx antennas over quasi-static Rayleigh fading channels. Moreover, the proposed codes would not cause any constellation expansion over QAM symbols in contrast with the quasi-orthogonal codes with constellation rotations
Design of Fractional Delay Filter, Differintegrator, Fractional Hilbert Transformer, and Differentiator in Time Domain With Peano Kernel

In this paper, we propose a fractional delay filter, an integer-order differintegrator, a fractional Hilbert transformer, and a fractional differintegrator. Through the time-domain analysis on the desired input and output signals of a linear time-invariant system, we derive a set of linear equations, which can be solved to obtain the coefficients of the desired filter. We also show that the difference between the desired output signal and the actual output of the system can be represented as the convolution of the derivative of the input signal and the Peano kernel.
Closed form variable fractional delay using FFT with transition band trade-off

In earlier paper, a conjugate symmetric frequency response has been presented to design the variable fractional delay filter by FFT, and has been proved to associate with the windowed sinc filter. However, this earlier method has no transition band design consideration. Therefore, in this paper, the trade-off between the transition band width and Gibbs phenomenon ripples is discussed, and an improved closed form design with additional transition band samples is introduced to reduce Gibbs phenomenon ripples. The proposed improved fractional delay method can also be efficiently realized by FFT using the tunable fractional delay parameter and transition band weighting factor. Several comparisons between the earlier method and the proposed improved method are also demonstrated. By measuring the largest peak ripple value in magnitude responses, our proposed method can achieve 9.43 times peak ripples reduction than the earlier method.
Visual Enhancement Using Constrained L0 Gradient Image Decomposition for Low Backlight Displays

We propose a system to enhance the visual quality of displays under low backlight. Our system can not only prolong the battery life but also enhance visual quality. First, we propose a constrained L0 gradient image decomposition to separate base layer and detail layer. Afterwards, we design a median-preserving gamma correction for compensation and a JND-based boosting for detail enhancement. Experimental results show that our system outperforms than the compared systems.
Design of arbitrary FIR log eigenfilters

An efficient method is proposed for the design of FIR filters with arbitrary log magnitude and phase responses in this paper. The method is based on an iterative weighted eigenfilter approach to obtain a least-squares approximation to the given log magnitude function, and the weighting function at each iteration is updated using the result of the previous iteration, which leads to the optimal approximation in the log Chebyshev sense. The method can be easily modified to approximate arbitrary log complex-valued frequency response, such as complex FIR log eigenfilters. Several examples are shown to demonstrate the effectiveness of this approach.
Color constancy via chromaticity neutralization: From single to multiple illuminants

In this paper, an improved color constancy approach is presented by considering the disadvantage of the well-known max-RGB algorithm: Only the unreliable maximum intensities are taken for illuminant estimation. To solve this problem, we propose the chromaticity neutralization process, which selects the representative pixels for robust illuminant computing. Moreover, to deal with the color deviation cases under multiple illuminant sources, we further present a procedure by first softly clustering the image pixels into several groups; the estimated illuminants from these groups are then combined based on the clustering weights to specifically determine the illuminant of each pixel. The experiments on two databases and web images demonstrate the effectiveness of our approach.
3D rotation estimation using discrete spherical harmonic oscillator transforms

This paper presents an approach to 3D rotation estimation using discrete spherical harmonic oscillator transforms (discrete SHOTs). Discrete SHOTs not only have simple and fast implementation methods but also are compatible with the existing angle estimation algorithms related to spherical harmonics. Discrete SHOTs of the rotated signal follow the same formulation to the Wigner-D matrix as spherical harmonics transforms. Thus, the spherical harmonics related algorithms could be utilized to discrete SHOTs without modification. Furthermore, compared to some existing methods, our approach with discrete SHOTs exhibits higher accuracy, higher precision and improved robustness to noise if the input signal is sampled uniformly on Cartesian grids. The phenomenon results from no interpolations in discrete SHOTs.
Color image segmentation using local histogram and self-organization of Kohonen feature map

Segmentation is an important step for image analysis, but a good segment algorithm which can handle color image with texture area and has less computation time is rare. We propose to use the local window image histogram, which is easy to compute and could quickly collect the information of neighbors, together with the Self-Organization of Kohonen Feature Map (SOFM) neural network, which can efficiently cluster data and has parallel hardware structure, as a segmentation kernel. Under the Euclidean distance function with input data normalization and the simplified Mahalanobis distance function, this algorithm will have very good segmentation results for natural images either full with texture or mixed with smooth scenes.
Sparse Fast Fourier Transform by downsampling

Sparse Fast Fourier Transform (sFFT) [1][2], has been recently proposed to outperform FFT in reducing computational complexity. Assume that an input signal of length N in the frequency domain is K-sparse, where K ≤ N. sFFT costs O(K logN) instead of O(N logN) in FFT. In this paper, a new fast sFFT algorithm is proposed and costs O(K logK) averagely without any operations being related to N. The idea is to downsample the original input signal at the beginning. Subsequent processing operates under downsampled signals, which length is proportional to O(K). However, downsampling possibly leads to “aliasing.” By shift theorem of DFT, the aliasing problem can be formulated as the “Moment-preserving problem.” In addition, a top-down iterative strategy combined with different downsampling factors further saves computational costs. Complexity analysis and experimental results show that our method outperforms FFT and sFFT.
Determination of circular arc length and midpoint by Hough transform

We propose a method to detect circular arcs, including the determinations of their centers, radii, lengths, and midpoints. The center, radius of a circular arc can easily be determined using circular Hough transform. But, the determinations of the arc midpoint and length are more complicated. Theoretical analysis of the centroid of the near-peak Hough transform data is presented. Then, the arc midpoint and length can be extracted from it.<<ETX>>
Image Quality Assessment Using Human Visual DOG Model Fused With Random Forest

Objective image quality assessment (IQA) plays an important role in the development of multimedia applications. Prediction of IQA metric should be consistent with human perception. The release of the newest IQA database (TID2013) challenges most of the widely used quality metrics (e.g., peak-to-noise-ratio and structure similarity index). We propose a new methodology to build the metric model using a regression approach. The new IQA score is set to be the nonlinear combination of features extracted from several difference of Gaussian (DOG) frequency bands, which mimics the human visual system (HVS). Experimental results show that the random forest regression model trained by the proposed DOG feature is highly correspondent to the HVS and is also robust when tested by available databases.
IIR multiple notch filter design based on allpass filter

A new technique for IIR multiple notch filter design is proposed. The specification of notch filter is first transformed into that of allpass filter. Then, we develop an effective approach to design this desired allpass filter. The realization of proposed notch filter is equivalent to the realization of an allpass filter. Due to the mirror-image symmetry relation between the numerator and denominator polynomials of allpass filter, the notch filter can be realized by a computationally efficient lattice structure with very low sensitivity. Moreover, some examples are presented to examine the effectiveness of proposed method.
Design of discrete Fractional Hilbert transformer in time domain

We propose a design of discrete Fractional Hilbert transformer. Through the time domain analysis of the ideal input and output signal of a LTI system, we derived equations which can be solved numerically for the filter's impulse response. The conventional Hilbert transformer is derived as a special case of the fractional Hilbert transformer. We also show that the difference between the designed system and the ideal system can be represented by the Peano kernel of the system. Some designing examples of the proposed filter are also illustrated.
Novel Inverse S Transform With Equalization Filter

The S transform is a useful linear time-frequency distribution with a progressive resolution. Since it is linear, it filters efficiently in a time-frequency domain by multiplying a mask function. Several different inverse algorithms exist, which may result in different filtering effects. The conventional inverse S transform (IST) proposed by Stockwell is efficient but suffers from time leakage during filtering. The recent algorithm proposed by Schimmel and Gallart has better time localization during filtering but suffers from a reconstruction error and the frequency leakage during filtering. In this paper, two new IST algorithms are proposed that have better time-frequency localization in filtering than the previous two methods.
Two-dimensional affine generalized fractional Fourier transform

As the one-dimensional (1-D) Fourier transform can be extended into the 1-D fractional Fourier transform (FRFT), we can also generalize the two-dimensional (2-D) Fourier transform. Sahin et al. ) have generalized the 2-D Fourier transform into the 2-D separable FRFT (which replaces each variable 1-D Fourier transform by the 1-D FRFT, respectively) and the 2-D separable canonical transform (further replaces FRFT by the canonical transform). Sahin et al., (see Appl. Opt., vol.31, no.23, p.5444-53, 1998), have also generalized it into the 2-D unseparable FRFT with four parameters. In this paper, we introduce the 1-D affine generalized fractional Fourier transform (AGFFT). It has even further extended the 2-D transforms described above. It is unseparable, and has, in total, ten degrees of freedom. We show that the 2-D AGFFT has many wonderful properties, such as the relations with the Wigner distribution, shifting-modulation operation, and the differentiation-multiplication operation. Although the 2-D AGFFT form seems very complex, in fact, the complexity of the implementation will not be more than the implementation of the 2-D separable FRFT. Besides, we also show that the 2-D AGFFT extends many of the applications for the 1-D FRFT, such as the filter design, optical system analysis, image processing, and pattern recognition and will be a very useful tool for 2-D signal processing.