nils-herrmann/clean_scirepeval huggingface dataset:
High-dynamic-range parallel multi-scale retinex enhancement with spatially-adaptive prior

We propose a parallel multi-scale retinex enhancement to synthesize a high-dynamic-range(HDR, HDR-like) image from a single low-dynamic-range (LDR) input. Since an image is composed of illumination and reflectance, we can enhance these two components to obtain our HDR results. First, we estimate the illumination from the input by optimizing a cost function with a spatially-adaptive edge prior. Then, we tune up the estimated illumination while enhance the reflection so as to synthesize the HDR result. In addition, we adopt parallel multi-scale acceleration for speed-up. Experimental results demonstrate that our retinex approach is promising as compared to the existing methods.
Spatially-varying super-resolution for HDTV

We propose a system to up-sample visual signals for high definition televisions (HDTVs). Although the original visual signals are degraded and limited, we still try to solve these problems by using super-resolution. First, we interpolate the visual signals with a edge taper to the desired size. Then, we combine L1 data term, L2 data term, Tikhonov-like regularizer and total variation regularizer with a saliency weighting for our L12TTV deblurring method. Adopting our L12TTV deblurring, we can remove the spatially-varying blurry conditions of the interpolated signals. Experimental results show that our system outperforms than comparisons in both image and video cases.
Very low bit-rate coding algorithm for stereo video with spatiotemporal HVS model and binary correlation disparity estimator

A strategy for efficiently coding stereo video sequences is investigated. To fully utilize the suppression and the contrast sensitivity property of the human visual system, a novel coding scheme with two special mechanisms, the spatiotemporal HVS model and the binary correlation disparity estimator, is proposed to efficiently reduce the video signal redundancy and the computational complexity, while maintaining a high subjective image quality. Compared with existing stereo video coding systems, the proposed coding scheme supports a lower transmission bit rate and has less computational complexity. The simulation results also show that the subjective image quality of the reconstructed full color stereo sequences at 0.25-0.4 bits per pixel (bpp) is satisfactory.
Closed-form design and efficient implementation of generalized maximally flat half-band FIR filters

In this letter, a closed-form expression for the impulse response of the generalized half-band (HB) maximally flat (MF) FIR filters is obtained by solving the linear equations of the MF conditions. Based on the resultant impulse responses, an efficient implementation structure is derived. The dynamic range of the multipliers of the new structure is shown to be greatly reduced in comparison to the one of the direct form impulse response.
Closed-form eigenvectors of the discrete Fourier Transform

Properties of eigenvectors and eigenvalues for discrete Fourier transform (DFT) are important for defining and understanding the discrete fractional Fourier transform (DFRFT). In this paper, we first propose a closed-form formula to construct an eigenvector of N-point DFT by down-sampling and then folding any eigenvector of (4N)-point DFT. The result is then generalized to derive eigenvectors of N-point DFT from eigenvectors of (k2N)-point DFT. To show an application of the proposed new closed-form DFT eigenvectors, Hermite-Gaussian-like (HGL) DFT eigenvectors which are much closer to the continuous Hermite-Gaussian functions (HGFs) are computed from existing HGL DFT eigenvectors of larger sizes with computer experiments.
A new discrete fractional Fourier transform based on constrained eigendecomposition of DFT matrix by Largrange multiplier method

This paper is concerned with the definition of the discrete fractional Fourier transform (DFRFT). First, an eigendecomposition of the discrete Fourier transform (DFT) matrix is derived by sampling the Hermite Gauss functions which are eigenfunctions of the continuous Fourier transform and by performing a novel error removal procedure. Then, the result of the eigendecomposition of the DFT matrix is used to define a new DFRFT. Finally, a numerical example is illustrated to demonstrate the proposed DFRFT is a better approximation to the continuous fractional Fourier transform than the conventional defined DFRFT.
Time and frequency split Zak transform for finite Gabor expansion

The relationship between the finite discrete Zak transform and the finite Gabor expansion are discussed in this paper. We present two DFT-based algorithms for computing Gabor coefficients. One is based upon the time-split Zak transform, the other upon the frequency-split Zak transform. These two methods are time and frequency dual pairs. Furthermore, we extend the relationship between the finite discrete Zak transform and the Gabor expansion to the 2-D case and compute 2-D Gabor expansion coefficients through the 2-D discrete Zak transform and 4-D DFT. Four methods can be applied in the 2-D case. They are time-time-split, time-frequency-split, frequency-time-split and frequency-frequency-split.
Fast Matching Pursuit Video Coding by Combining Dictionary Approximation and Atom Extraction

In this paper, we propose a systematic approach that approximates a target dictionary to reduce the complexity of a matching pursuit encoder. We combine calculation of the inner products and maximum atom extraction of a matching pursuit video coding scheme based on eigendictionary approximation and tree-based vector quantization. The approach makes the codec design and optimization cleaner and more systematic than previous dictionary approximation methods. We vary the quality of approximation to demonstrate the tradeoff between computational complexity and coding efficiency. The experiment results show that our codec achieves speed-up factors of up to 100 with a performance loss of less than 0.1 dB. We use double-stimulus impairment scale scores to evaluate the perceptual quality of our approach for different levels of complexity.
Design of Variable Two-Dimensional FIR Digital Filters by McClellan Transformation

In this paper, the technique of McClellan transformation is applied to design variable 2-D FIR digital filters. Compared with the conventional transformation, the 2-D transformation subfilter and the 1-D prototype filter are designed such that their frequency characteristics are adjustable. Moreover, they are tunable by the same variable parameter, so the variable characteristics of 1-D prototype filters are coincident with those of 2-D subfilters. Several examples, including variable fan filters, variable circularly symmetric filters, and variable elliptically symmetric filters with arbitrary orientation, are presented to demonstrate the effectiveness and the flexibility of the presented method.
Programmable fractional sample delay filters with flatness compromise between magnitude response and group delay

In this paper, a new design of fractional sample delay filter is presented. This method is based on the Stancu polynomial, which possesses an extra parameter /spl alpha/. Under special choice of this parameter, the results obtained are identical to previous ones based on Lagrange interpolation formula. Much more flatness of group-delay response can be achieved at the sacrifice of the filter magnitude response. Thus, this method provides designers with more flexibility for trading between these two performance criteria.
Direct N-point DCT computation from three adjacent N/3-point DCT coefficients

An efficient method for computing a length-N DCT given three consecutive length-N/3 DCTs is proposed. This method differs from previous ones in that it reduces considerable arithmetic operations and uses only length-N/3 DCTs instead of length-N DCTs. We also find its great applications in fractional scaling of a DCT-based image by the factor of N/2/sup /spl alpha//3/sup /spl beta//. This would be very useful in HDTV standard, whose display size is usually 16:9. The comparison with conventional methods is provided in this paper.
Virtual restoration of ancient Chinese paintings using color contrast enhancement and lacuna texture synthesis

This work presents a novel algorithm using color contrast enhancement and lacuna texture synthesis is proposed for the virtual restoration of ancient Chinese paintings. Color contrast enhancement based on saturation and de-saturation is performed in the u'v'Y color space, to change the saturation value in the chromaticity diagram, and adaptive histogram equalization then is adopted to adjust the luminance component. Additionally, this work presents a new patching method using the Markov random field (MRF) model of texture synthesis. Eliminating undesirable aged painting patterns, such as stains, crevices, and artifacts, and then filling the lacuna regions with the appropriate textures is simple and efficient. The synthesization procedure integrates three key approaches, weighted mask, annular scan and auxiliary, with neighborhood searching. These approaches can maintain a complete shape and prevent edge disconnection in the final results. Moreover, the boundary between original and synthesized paintings is seamless, and we are unable to distinguish in which the undesirable pattern appears.
Power-scalable multi-layer halftone video display for electronic paper

Video halftoning is a key technology for use in the new display device, electronic paper (e-paper). One challenging issue is how to save the limited power of mobile e-paper device when a halftone video is displayed with various frame rates. In this paper, we propose a power-scalable multi-layer halftone video display scheme, which is composed of layer coding, non-uniform sampling, and flicker rate reduction. Our method not only efficiently save power over the state of the art video halftoning technology but also keep the quality of halftone video nearly unchanged when power saving is additionally considered. Experimental results demonstrate the effectiveness of the proposed method.
Narrowband Notch Filter Using Feedback Structure Tips & Tricks

The design of a notch filter poses challenges in managing the tradeoff between distortion in the passband and the notch band. The ideal notch filter has a 3-dB notch bandwidth (BW) equal to zero in the notch band and the unity gain in the passband. Therefore, the design objective is to shrink the BW as small as possible while preserving the gain as close to one as possible. The task of a notch filter is to eliminate interference while preserving the target broadband signal. These filters have many applications for narrowband interference removal in biomedical engineering , speech processing , image processing , , and communication . In this article, we describe two ways to implement a notch filter. First, we present a simple notch filter and then illustrate why its performance is less than ideal. Next, we present a trick to apply a novel feedback structure to that notch filter, which improves its performance to nearly ideal. With the help of the feedback structure, we obtain an adjustable parameter. By tuning this parameter, different characteristics of the notch filter are obtained due to the change of its poles' position.
Reversible Joint Hilbert and Linear Canonical Transform Without Distortion

Generalized analytic signal associated with the linear canonical transform (LCT) was proposed recently by Fu and Li [“Generalized Analytic Signal Associated With Linear Canonical Transform,” Opt. Commun., vol. 281, pp. 1468-1472, 2008]. However, most real signals, especially for baseband real signals, cannot be perfectly recovered from their generalized analytic signals. Therefore, in this paper, the conventional Hilbert transform (HT) and analytic signal associated with the LCT are concerned. To transform a real signal into the LCT of its HT, two integral transforms (i.e., the HT and LCT) are required. The goal of this paper is to simplify cascades of multiple integral transforms, which may be the HT, analytic signal, LCT or inverse LCT. The proposed transforms can reduce the complexity when realizing the relationships among the following six kinds of signals: a real signal, its HT and analytic signal, and the LCT of these three signals. Most importantly, all the proposed transforms are reversible and undistorted. Using the proposed transforms, several signal processing applications are discussed and show the advantages and flexibility over simply using the analytic signal or the LCT.
Discrete Inverse $S$ Transform With Least Square Error in Time-Frequency Filters

The S transform is useful in time-frequency analysis. Many inverse S transform algorithms have been proposed with different filtering properties in the time-frequency spectrum. In this paper, the transformation matrices of the S transform and two novel least square inverse algorithms are proposed. The first one minimizes the global mean square error of the entire time-frequency spectrum, and the second one considers only the specific interesting time-frequency regions and is more flexible. The proposed inverse algorithms can provide more stable and better performance than the existing ones.
Closed-form design of maximally flat R-regular Mth-band FIR filters

In this paper, we derive some properties of maximally flat R-regular Mth-band FIR filters. We show that the R-regularity implies maximally flat frequency response at /spl omega/=0. The R-regular constraints are a set of linear equations with complex coefficients. We can convert these complex-value equations to equivalent ones with only real coefficients. We also show that it is possible to completely determine the filter coefficients by R-regularity. Design examples are presented to illustrate the R-regularity properties and the effectiveness of the proposed approach.
Complex eigenfilter design of arbitrary complex coefficient FIR digital filters

The real eigenfilter approach is extended to complex cases for designing arbitrary complex finite impulse response (FIR) filters. By minimizing a quadratic measure of the error in the passband and stopband, a complex eigenvector of an appropriate complex, Hermitian symmetric, and positive-definite matrix is computed to get the filter coefficients. Several arbitrary magnitude and phase FIR filters, such as multiple passband complex filters and staircase-delay allpass phase equalizers, can be easily designed by this approach. This method can be easily extended to design 2-D complex FIR filters. If an appropriate iterative process is used, equiripple filters in the complex Chebyshev sense can be obtained. Several numerical design examples demonstrate the usefulness of the approach.
A novel music similarity measure system based on instrumentation analysis

A music similarity measure system based on the instrumentation information is proposed in this paper. We combine our previous instrumentation analysis algorithm with a newly designed similarity measure system, which aims at comparing songs solely on their instrumentation content. Several midlevel features are designed and integrated along with the existing low-level feature MFCCs. The weighted distance is then applied to rank the similarity of songs in pair inside the music database. We evaluate its performance by ten-fold cross validation on a Western classical music database. The objective test shows the incorporation of new mid-level features can increase the correctness of the composer classification task by approximately 10%.
Efficient Bit and Digital Reversal Algorithm Using Vector Calculation

This correspondence describes an efficient bit and digital reversal algorithm using vector calculation. It is much more efficient and simple than calculating the bit and digital reversal sequentially one by one using for-loop. An auxiliary small-size seed table can also be used for building up larger table in our algorithm to speed up the computation time. It will be very useful for data shuffling in radix-2 and radix-4 fast Fourier transforms
Intrinsic Integer-Periodic Functions for Discrete Periodicity Detection

In this letter we focus on discrete integer-periodic signals, whose periodicity are different from the periodicity of continuous periodic signals in many aspects. We introduce a class of discrete periodic signals called intrinsic integer-periodic function (IIPF). An IIPF contains only a single period in terms of downsampling, which leads to some interesting properties for analyzing periodic components from a discrete signal. We show that one can use Ramanujan sum to decompose discrete periodic signals into IIPF components. Finally, we also propose an integer periodic spectrum rather than frequency spectrum. Our results show that the proposed integer periodic spectrum outperforms the conventional Ramanujan Fourier transform.
Equiripple phase design of complex all-pass networks

A new method is proposed for designing complex all-pass IIR filters, the all-pass IIR filters with complex coefficients, in this paper. By minimizing the integration of certain square phase error over interested frequencies, an eigenvector of an appropriate real, symmetric and positive-definite matrix is computed to get the filter coefficients. The stability is achieved by specifying properly the desired phase specifications. If an appropriate iterative process is used, equiripple complex all-pass filter design can be obtained. The method is simple and the performance is comparable to the existing methods. Several examples are presented to demonstrate the effectiveness of the approach.
Improved Methods for the Design of Variable Fractional-Delay IIR Digital Filters

In this paper, both methods of magnitude-oriented design and delay-oriented design for variable fractional-delay (VFD) infinite impulse response (IIR) filters are proposed. In the former, the objective error function is formed by including root-mean-square error function of variable frequency response and the stability error constrained function, such that the designed filters are stable. As for the second part of this paper, it is desirable to minimize the root-mean-square error of variable group-delay response while the magnitude response and stability can be preserved. Hence, except those stated above, the root-mean-square error function of variable group-delay response is further included in the objective error function. However, these induced problems are highly nonlinear, so iterative methods are proposed to overcome them. Several design examples are presented to demonstrate the features of these design methods, including concerns among VFD finite impulse response (FIR) filters, VFD allpass filters and VFD IIR filters as well as the designed results of both methods.
Two-Dimensional Partially Differential Cepstrum and Its Applications on Filter Stabilization and Phase Unwrapping

A new type of differential cepstrum (DC) named as partially DC (PDC) is introduced. While compared with the previously defined DC, the PDC saves half the computational complexity since only one dimension of the partial derivative is considered. Nevertheless, for the calculation of the complex cepstrum (CC), using the PDC avoids the phase-unwrapping routine as well. One application is to construct the minimum-phase sequence from a mixed-phase one through a windowing technique, which can be further applied to filter stabilization. Another application is performing phase unwrapping on 2-D phase data to which we propose a much simpler technique using the PDC. These applications can be implemented in a more efficient and convenient way with the PDC than with the traditional DC.
Color image processing by using binary quaternion-moment-preserving thresholding technique

This paper presents a new moment-preserving thresholding technique, called the binary quaternion-moment-preserving (BQMP) thresholding, for color image data. Based on representing color data by the quaternions, the statistical parameters of color data can be expressed through the definition of quaternion moments. Analytical formulas of the BQMP thresholding can thus be determined by using the algebra of the quaternions. The computation time for the BQMP thresholding is of order of the data size. By using the BQMP thresholding, quaternion-moment-based operators are designed for the application of color image processing, such as color image compression, multiclass clustering of color data, and subpixel color edge detection. The experimental results show that the proposed operator for color image compression can have output picture quality acceptable to human eyes. In addition, the proposed edge operator can detect the color edge at the subpixel level. Therefore, the proposed BQMP thresholding can be used as a tool for color image processing.
Effective palette indexing for image compression using self-organization of Kohonen feature map

The process of limited-color image compression usually involves color quantization followed by palette re-indexing. Palette re-indexing could improve the compression of color-indexed images, but it is still complicated and consumes extra time. Making use of the topology-preserving property of self-organizing Kohonen feature map, we can generate a fairly good color index table to achieve both high image quality and high compression, without re-indexing. Promising experiment results will be presented
Relationships among digital one/half band filters, low/high order differentiators, and discrete/differentiating Hilbert transformers

There exists a close relationship among digital one-/half-band filters, low-/high-order differentiators, and discrete/differentiating Hilbert transformers. A complete picture of their interrelationships and conversions between each other is presented. A useful table and some block diagrams have been developed for their impulse responses' connections, and a design example is given for illustration.
Design of complex FIR filters with arbitrary complex frequency responses by two real Chebyshev approximations

The well-known Parks-McClellan program can only design linear phase real FIR filters, and the Remez exchange algorithm is not readily applied for general complex FIR filter design. Here the problem of designing complex FIR filters is solved by dividing the original complex approximation into two real ones such that the Remez exchange algorithm can be applied by slightly modifying the Parks-McClellan-McCalling program. Arbitrary frequency response complex FIR filters and complex all-pass filters can be easily designed by this efficient technique. This approach has several practical advantages such as fast design time and easy implementation with satisfactory performance.
A new method for the design of variable comb filters

In this paper, design of wide-range variable fractional-delay (WR-VFD) finite impulse response (FIR) digital filters is proposed and then is applied to implement comb filters. However, when it is applied to construct a variable comb filter which is an IIR system, stability constraint must be considered, and the technique of quadratic programming and a strategy of sampling points for stability constraint are used to design a stable variable comb filter.
Discrete fractional Fourier transform

The continuous fractional Fourier transform (FRFT) represents a rotation of signal in time-frequency plane, and it has become an important tool for signal analysis. A discrete version of fractional Fourier transform has been developed but its results do not match those of continuous case. In this paper, we propose a new version of discrete fractional Fourier transform (DFRFT). This new DFRFT will provide similar transforms as those of continuous fractional Fourier transform and also hold the rotation properties.