nils-herrmann/clean_scirepeval huggingface dataset:
A novel 2-D window for spectral estimation

A novel 2-D window can be easily generated by the McClellan transform of Tseng's 1-D window. The transformed window has nearly circularly symmetric frequency response and preserves the features and flexibility of Tseng's 1-D prototype window. It can independently control the pattern falloff rate, the sidelobe level, and the depth of a steerable wide dip. Examples of detecting multiple 2-D closely spaced sinusoids have demonstrated the superiority of this novel 2-D window.
Viewing-Distance Aware Super-Resolution for High-Definition Display

In this paper, we propose a novel algorithm for high-definition displays to enlarge low-resolution images while maintaining perceptual constancy (i.e., the same field-of-view, perceptual blur radius, and the retinal image size in viewer's eyes). We model the relationship between a viewer and a display by considering two main aspects of visual perception, i.e., scaling factor and perceptual blur radius. As long as we enlarge an image while adjust its image blur levels on the display, we can maintain viewer's perceptual constancy. We show that the scaling factor should be set in proportion to the viewing distance and the blur levels on the display should be adjusted according to the focal length of a viewer. Toward this, we first refer to edge directions to interpolate a low-resolution image with the increasing of viewing distance and the scaling factor. After images are interpolated, we utilize a local contrast to estimate the spatially varying image blur levels of the interpolated image. We then further adjust the image blur levels using a parametric deblurring method, which combines L1 as well as L2 reconstruction errors, and Tikhonov with total variation regularization terms. By taking these factors into account, high-resolution images adaptive to viewing distance on a display can be generated. Experimental results on both natural image metric and user subjective studies across image scales demonstrate that the proposed super-resolution algorithm for high-definition displays performs favorably against the state-of-the-art methods.
FIR filter designs with linear constraints using the eigenfilter approach

Conventionally, the eigenfilter approach has been successfully used to design a linear phase FIR filter without adding, any constraint, such as a low-pass filter, differentiator, and Hilbert transformer. When a constraint is incorporated in the eigenfilter design, only some special examples have been considered. The Nyquist filter is a typical example. In this paper, we first develop an eigenfilter approach to design a linear phase FIR filter in conjunction with general linear constraints. Then, we extend the proposed approach to the arbitrary FIR filter design with general linear constraints. Two design examples are presented to demonstrate the effectiveness of our approaches.
Closed-Form Design of Maximally Flat IIR Hilbert Transformer With Integer Delay

This paper presents the closed-form designs of an infinite-impulse-response (IIR) Hilbert transformer with an integer delay. The maximally flat criterion is applied at the midband frequency π/2. These designs are further categorized into eight types according to the filter orders and the delay values being even or odd. Their coefficients can be explicitly solved in closed form. A recursive relation also exists, facilitating the computation of these coefficients. Moreover, under the suggested relations and formula for the design parameters based on the Eneström-Kakeya theorem, we can obtain a satisfactory stable IIR Hilbert transformer.
Wavelet transform and scale space filtering of fractal images

In this correspondence, we consider wavelet transform and scale space filtering as special cases of general scale shift mapping (SSM). Then, the SSM is used as a tool for characterizing the geometrical complexity of uniform fractals. This tool can reveal the construction rule of fractals and estimate fractal dimension. Finally, we use the results obtained from scale shift mapping to estimate iterated function system (IFS) codes of a class of fractal images. Some examples have been illustrated to demonstrate its good performance.
Two-dimensional partially differential cepstrum and minimum-phase sequence construction

A new partially differential cepstrum is defined, which can be regarded as a new type of differential cepstrum. It saves half computational complexity compared with the previously defined differential cepstrum since only one dimension of partial derivative is considered. Nevertheless, this suffices for avoiding phase-unwrapping in complex-cepstrum calculation. As an application of complex cepstrum, we also introduce a windowing technique to construct the minimum-phase sequence from a mixed-phase one.
Multiple blocks matching pursuit update algorithm for low bit rate video coding

Matching pursuit (MP) is a greedy algorithm that decomposes a signal into a linear combination of bases within an over-complete dictionary. The MP algorithm is usually only approximated due to its massive computational complexity. By approximating a residual in a subspace, we propose a multiple blocks MP update algorithm for video coding that achieves a faster and better MP approximation than traditional algorithms. As the subspace is dependent on a residual, our algorithm is content-dependent. We evaluate the coding performance, including the peak signal-to-noise ratio, runtime, and subjective quality, of our algorithm and compare it with traditional MP algorithms.
Design of nonsquare 2D FIR filters by transformations

McClellan's transformations for 2D FIR filter design are sliced into several 1D frequency transforms for linear phase variable filters. Each transform maps 1D prototype FIR filter into several one dimensional variable cut-off digital filters in the 2D frequency plane; This approach is equivalent to the conventional McClellan's transformation, however the complicated 2D transformation steps are reduced into the simple 1D forms, the algorithm is much easier to implement and has additional advantage to design the nonsquare 2D FIR filters.
Design of arbitrary cutoff 2-D diamond-shaped FIR filters using the Bernstein polynomial

In this paper, we propose a design of two-dimensional (2-D) linear-phase, diamond-shaped (DS) finite impulse response (FIR) filters by using Bernstein polynomials. Although the one-dimensional (1-D) FIR filter designed by the Bernstein polynomials has been well investigated, this approach has not been broadly applied to 2-D filter design yet. We present a novel method of designing the 2-D FIR DS filter. In order to be approximated by a 2-D Bernstein polynomial, the 2-D symmetrical frequency response is transformed into a new domain. The key observation is that the region of support of the transformed frequency response is not diamond-shaped. The boundary of the new region of support represents an ellipse, a circle, or a line, and is analytically derived. The resultant magnitude responses are flat in the passband and stopband.
Image indexing using 3D model for image retrieval

Content-based image retrieval (CBIR) is an interesting but difficult topic of research. It uses the visual features to achieve the image searching on database. In this paper, we propose an image indexing for CBIR based on color feature, which consider both the computational complexity and the spatial relationship. We use a 3D mathematical model to design the color codebook and exploit the feature of the query image to adopt it. In the experiments, we discuss the three parameters affecting the performance and find out the corresponding optimal value to raise the retrieval speed and accuracy. Besides, we also demonstrate that the proposed scheme is robust for some image distortions and best matches human perception overall.
Maximally flat allpass fractional Hilbert transformers

Recently, a generalization of the Hilbert transformer, the fractional Hilbert transformer, was defined and developed. In this paper, we propose a design of the allpass filter to realize the fractional Hilbert transformer based on the maximally flat approximation to the desired phase response. The coefficients are solved analytically for the traditional Hilbert transformer which is a special case of the fractional Hilbert transformer. Based on the closed-form coefficients, we show that the maximally flat allpass Hilbert transformers are stable. Design examples indicate that the proposed filters exhibit good approximation to the desired frequency response.
Novel error concealment method with adaptive prediction to the abrupt and gradual scene changes

In this paper, the impact of scene change on the conventional error concealment method is addressed and a novel error concealment method is proposed to improve the insufficiency of the conventional temporal error concealment algorithm due to the occurrence of scene change. Combining with the low complexity scene change detection algorithm using macroblock type information, the corrupt blocks resulting from bit errors are concealed either temporally or spatially depending on whether or not an abrupt scene change is found. In the case of gradual scene change, a novel error concealment method of interpolation and extrapolation is proposed to utilize the linear property of gradual scene change sequence, and effectively reduce the concealment error in comparison with the conventional algorithm. A great improvement of about 3 to 5 dB PSNR on average and 6 to 8 dB in some cases is obtained with very little memory and computation overhead.
Saliency detection using superpixel belief propagation

We propose a method to detect saliency from a single image using feature extraction and superpixel belief propagation. We observe that the previous works are hard to deal with the intrinsic material discontinuity and non-homogeneous color distribution within an object or a region. Motivated by this observation, we bring the belief propagation into the saliency detection. First, we separate the image into middle-level superpixels and also extract the low-level feature within each superpixel. Then, we build up a Markov-Random-Field (MRF) on the middle-level super-pixels and adopt propagation technique to optimize the superpixel saliency. Afterward, we refine this middle-level solution to per-pixel saliency map. Experimental results demonstrate that our proposed method is promising as compared to the state-of-the-art methods in both MSRA-1000 and SED datasets.
Design of 2-D quadrature mirror FIR filters for image subband coding

A new 2-D subband coding scheme is proposed. Two-dimensional quadrature mirror filters (QMF's) can be efficiently designed by a separable product of identical 1-D QMF filters. Smith, Barnwell, and Mintzer's 1-D QMF design technique is carefully chosen and used in our 2-D subband filters. The resultant 2-D QMF filters and subband coder allow for "exact" reconstruction free of aliasing and of phase and frequency distortion, and will be very useful for image subband coding applications.
Split-vector radix 2-D fast Fourier transform

The split vector radix is used to develop a 2-D fast Fourier transform (FFT) algorithm; it is performed "in-place," and requires no matrix transpose operation. This method greatly improves the conventional vector radix 2-D FFT; an overall saving of about 23 percent in complex multiplications for a typical 2048 \times 2048 array could be obtained.
Enhancement of uneven lighting text image using line-based Empirical Mode Decomposition

Non-uniform light distribution problems often arise in the text images taken by digital camera. In this paper, we propose a novel technique for text image uneven lighting removal using Empirical Mode Decomposition (EMD). The EMD is local, adaptive and useful for analyzing non-linear and non-stationary signals. In this method, we decompose images by EMD and get the background level locally and adaptively. This algorithm can enhance local contrast in the image while removing shadows for black-and-white text images. In addition, this work can be very helpful for text recognition. The experimental results show that the proposed approach can effectively enhance text images more readable under uneven lighting.
Two dimensional adaptive filter using Laguerre function

A new two dimensional (2D) adaptive filter structure is developed. It is based on modeling the impulse response of the 2D IIR systems as a finite linear combination of a set of 2D Laguerre orthonormal functions. When it is required to identify a system with a long impulse response, computer simulation shows that the 2D Laguerre filter has a better performance than the conventional 2D FIR filter at the same computation cost.<<ETX>>
Tridiagonal Commuting Matrices and Fractionalizations of DCT and DST Matrices of Types I, IV, V, and VIII

In this paper, we first establish new relationships in matrix forms among discrete Fourier transform (DFT), generalized DFT (GDFT), and various types of discrete cosine transform (DCT) and discrete sine transform (DST) matrices. Two new independent tridiagonal commuting matrices for each of DCT and DST matrices of types I, IV, V, and VIII are then derived from the existing commuting matrices of DFT and GDFT. With these new commuting matrices, the orthonormal sets of Hermite-like eigenvectors for DCT and DST matrices can be determined and the discrete fractional cosine transform (DFRCT) and the discrete fractional sine transform (DFRST) are defined. The relationships among the discrete fractional Fourier transform (DFRFT), fractional GDFT, and various types of DFRCT and DFRST are developed to reduce computations for DFRFT and fractional GDFT.
Discrete fractional Hartley and Fourier transforms

This paper is concerned with the definitions of the discrete fractional Hartley transform (DFRHT) and the discrete fractional Fourier transform (DFRFT). First, the eigenvalues and eigenvectors of the discrete Fourier and Hartley transform matrices are investigated. Then, the results of the eigendecompositions of the transform matrices are used to define DFRHT and DFRFT. Also, an important relationship between DFRHT and DFRFT is described, and numerical examples are illustrated to demonstrate that the proposed DFRFT is a better approximation to the continuous fractional Fourier transform than the conventional defined DFRFT. Finally, a filtering technique in the fractional Fourier transform domain is applied to remove chirp interference.
The generalized fractional fourier transform

A new transform, called the generalized fractional Fourier transform (gFrFT), is proposed. Originally, the eigenfunctions of the fractional Fourier transform (FrFT) are known as the Hermite Gaussian functions (HGFs). Besides, in optics, the HGFs are generalized to be the generalized Hermite Gaussian functions (gHGFs) and their adjoint functions (AgHGFs). Therefore, we can define the gFrFT by the eigenvalues of the FrFT and the eigenfunctions (gHGFs/AgHGFs) in the analysis or synthesis step. Four types of the gFrFT are defined and discussed. The integral forms of the gFrFTs are derived and they are closely related to some popular transforms, such as the Fourier transform (FT), the FrFT, and the complex linear canonical transform (CLCT). We can also extend the FT and the FrFT to the standard and elegant versions. Finally, some properties of the gFrFT are discussed.
Integer 2-D Discrete Fourier Transform Pairs and Eigenvectors using Ramanujan’s Sum

A novel method to generate integer 2-D discrete Fourier transform (DFT) pairs and eigenvectors was proposed. Using projection slice theorem and Ramanujan's sum, the 2-D spatial signal is decomposed into 2-D gcd-delta functions which contain only zeroes and ones. The 2-D DFT of 2-D gcd-delta functions are also integers. The integer 2-D DFT pairs can be applied to obtain integer 2-D DFT eigenvectors and 2-D period detection. The connection between 2-D gcd-delta function and multidimensional Ramanujan's Sum is also illustrated with two numerical examples.
Legendre Ramanujan Sums transform

In this paper, Legendre Ramanujan Sums transform(LRST) is proposed and derived by applying DFT to the complete generalized Legendre sequence (CGLS) matrices. The original matrix based Ramanujan Sums transform (RST) by truncating the Ramanujan Sums series is non-orthogonal and lack of fast algorithm, the proposed LRST has orthogonal property and O(Nlog2V) complexity fast algorithm. The LRST transform matrix is a sparse matrix and can be calculated with only additions and multiplications with more improvement in efficiency. It is suitable for image compression and transform coding. Meanwhile the LRST is useful to analyze to periodic signal especially for already known periodic sequences.
Two dimensional IIR digital notch filter design

In this paper, the two dimensional (2D) IIR digital notch filter design problem is investigated. First, we develop a simple algebraic method for 2D IIR notch filter design. This approach not only has closed-form transfer function but also satisfies the bounded-input/bounded-output (BIBO) stability condition. Next, we apply the 2D notch filter to eliminate sinusoidal/narrowband interferences superimposed on an image. Simulation results are presented to demonstrate the effectiveness of this approach.
Temporal Frequency of Flickering-Distortion Optimized Video Halftoning for Electronic Paper

Video halftoning is a key technology for use in electronic paper (e-paper) or smart paper, which is an emerging display device that has received considerable attention recently. In this paper, a temporal frequency of flickering-distortion optimized video halftoning method is proposed. We first uncover three visual defects that conventional neighboring frame referencing-based video halftoning methods, due to their sequential changes of reference frames, will encounter. To deal with the problem, we then propose a reference frame update per GOP-based error diffusion video halftoning method based on a flickering sensitivity-based human visual model. To efficiently compromise between average temporal frequency of flickering (ATFoF) and visual quality, temporal frequency of flickering-distortion (TFoFD) is presented as a metric for video halftoning performance evaluation. Based on the proposed probability model of video halftoning, the TFoFD curve can be accurately estimated to optimize the tradeoff between quality and ATFoF before the video is halftoned. Our temporal frequency of flickering-distortion optimization strategy can also be applied to other video halftoning schemes for performance improvement. Experimental results and comparisons with known methods demonstrate the effectiveness of our video halftoning method.
A moment-based approach for deskewing rotationally symmetric shapes

The covariance matrix of a pattern is composed by its second order central moments. For a rotationally symmetric shape, its covariance matrix is a scalar identity matrix. In this work, we apply this property to restore the skewed shape of rotational symmetry. The relations between the skew transformation matrix and the covariance matrices of original and skewed shapes are derived. By computing the covariance matrix of the skewed shape and letting the covariance matrix of the original shape be a scalar identity matrix, the skew transformation matrix can be solved. Then, the rotationally symmetric shape can be recovered by multiplying the inverse transformation matrix with the skewed shape. The method does not rely on continuous contours and is robust to noise, because only the second-order moments of the input shape are required. Experimental results are also presented.
A technique for transient suppression of IIR notch filter

A technique for suppressing the transient states of IIR notch filters is presented. This technique mainly uses the vector projection to find the best initialization of a notch filter. When a notch filter is used to cancel 60 Hz interference in the recording of electrocardiograms (ECG), the performance of the notch filter with transient suppression is better than that of the notch filter with arbitrary initialization. The improvements realized by this technique is at the cost of little additional computational load at the beginning of filtering.<<ETX>>
Modified Inverse s Transform for Filtering in Time-Frequency Spectrum

The S transform is a powerful linear time-frequency representation, and it is especially useful for filter in the time-frequency spectrum. To improve the time resolution of the filter applications, Schimmel and Gallart have proposed a new method for inverse S transform. This new method performs much better than the original in time localization with time-frequency filters. However, there exists some distortion of the inverse transformed signal that it will be enhanced in the positive but suppressed in the negative frequency part. In this paper we will demonstrate the distortion and propose a modified method to derive the correct inverse transformed signal and provide satisfactory time localization in filtering.
Eigen-approach for designing FIR filters and all-pass phase equalizers with prescribed magnitude and phase response

An effective eigenfilter approach is proposed for designing FIR filters with complex-valued frequency responses. By minimizing a quadratic measure of the error in the frequency band, an eigenvector of an appropriate matrix is computed to get the filter coefficients. The algorithm is easy and optimal in the least squares sense; it is used to design to major classes of FIR filters, including multiband filters, differentiators, Hilbert transformers, and all-pass phase. Several examples and comparisons to the existing linear programming methods are presented to demonstrate the flexibility and effectiveness of this approach.
Census-based vision for auditory depth images and speech navigation of visually impaired users

In neuroscience and psychology, visual imagery is the subjective experience of seeing in the absence of visual stimulation. Someone may experience touch or sound as a result of visual imagery. In this paper, a new visual image aid which can provide a different way to visualize the image for visually impaired users is proposed. It is done by applying the depth image to an Image-To-Sound Mapping (ITSM) system. The proposed algorithm utilizes a sparse Census transform (SCT) and color segmentation to obtain an illuminationinvariant depth image. The depth image is applied to the ITSM system and then a clear and simple sound output is obtained for constructing a mental image. Moreover, the reliable three-dimensional (3D) data of close objects are extracted and interpreted as a semantic speech output. Experimental results show that visually impaired users can perceive the image easily and without training by adding verbal description to the visually image aid. In good and poor illuminated environments, the performance is 82% and 80% respectively. The performance of our proposed systems was not influenced by various lighting. All subjects also commented that the systems would be potentially useful1.
Instrumentation analysis and identification of polyphonic music using beat-synchronous feature integration and fuzzy clustering

In this paper, a music instrumentation analysis and identification method is proposed. In contrast to existing systems, it tries to identify the whole instrument set in polyphonic music and also decide whether each instrument actually dominates at a particular moment or not, but without calculating the exact pitch, onset timing, or the volume of each note. Moreover, it does not require the music source separation in advance. We address this problem by incorporating the beatsynchronous scheme with fuzzy clustering to analyze the instrument components. Experiments show that the instrument identification process results in an 85.19% averaging recognition rate, which is comparable with other existing systems. In addition, it generates the extra time-varying instrumentation information. This information can be considered as a new mid-level feature in music information retrieval systems.