nils-herrmann/clean_scirepeval huggingface dataset:
Analytic closed forms for designing higher order digital differentiators by eigen-approach

The eigenfilter method has recently been proposed for designing higher-order differentiators very effectively. The design method is based on the computation of an eigenvector of an appropriate real, symmetric, and positive-definite matrix. The elements of this matrix are usually evaluated by very time-consuming numerical integration. In the present work, the authors present simple analytical closed-form formulas to compute these matrix-elements very efficiently. Hence, the eigenfilter approach for differentiators becomes much easier and more accurate than before, and the design time is reduced greatly with the larger filter length. Several design examples are used to illustrate the effectiveness of this approach.<<ETX>>
IIR multiple notch filter design based on allpass filter

A real coefficient IIR notch filter design problem is investigated. The notch filter specification is first transformed into that of an allpass filter. Then, we develop an effective approach to design this desired allpass filter. The realization of the 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 the allpass filter, the notch filter can be realized by a computationally efficient lattice structure with very low sensitivity. Moreover, some design and application examples are presented to examine the effectiveness of proposed method.
Removing rain and snow in a single image using saturation and visibility features

Rain and snow are two of the major obstacles in processing the photograph captured in the outdoor bad weather conditions. Rain and snow will cause the performance of vision algorithm become worse. There are a lot of methods have been proposed to reduce the raindrops and snowflakes in video. However, how to remove rain and snow and keep the detail of the background in a single image is still quite challenging since it is hard to detect the pixels of rain and snow. In this paper, we proposed a new method based on features on saturation and visibility. The results show that it can achieve better performance than previous methods.
Design of arbitrary complex coefficient FIR digital filters by complex weighted least squares approximation

Real weighted least squares (WLS) approach is extended to complex cases for designing arbitrary complex FIR filters. The method is based on an iterative complex WLS approach to obtain a least squares approximation to the desired complex frequency responses, and the weighting function at each iteration is updated using the result of the previous iteration, which leads to the optimal approximation in the complex Chebyshev sense. Some numerical design examples such as single-passband filters and complex all-pass filters are presented, which demonstrate the usefulness of the present approach.
Efficient design of 2-D multiplierless FIR filters by transformation

This paper deals with the design of 2-D multiplierless FIR digital filters. First, a special class of multiplierless 1-D FIR filters is designed with coefficients which are a sum or difference of power of two. This is then mapped into 2-D multiplierless FIR filters by the 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 2-D FIR filters is very attractive and efficient.
Elimination of AC interference in electrocardiogram using IIR notch filter with transient suppression.

In this paper, a technique for suppressing the transient states of IIR notch filter is investigated. This technique uses the vector projection to find better initial values for notch filters. When a notch or comb filter is used to eliminate power line (AC) interference in the recording of electrocardiograms (ECG), the performance of the notch filter with transient suppression is better than that of the conventional notch filter with arbitrary initial condition. The improvements with this technique are at the cost of additional computation load at the beginning of filtering.
Energy concentration enhancement using window width optimization in S transform

The S transform is a useful time-frequency analysis algorithm. Based on the concentration measure, a method to optimize the window width in the S transform has been proposed by previous studies along with some examples demonstrating its effectiveness. However, it is found that although this method performs well for the high and middle frequency signals, it may fail for the low frequency ones. In this paper, a new method, which is more flexible than the previous one, is proposed to deal with this problem. Comparison of these two methods for energy concentration enhancement is also provided. Experimental result shows that the proposed method achieves higher energy concentration in comparison to the previous one and the original ST.
Scene-effect detection and insertion MPEG encoding scheme for video browsing and error concealment

For an MPEG coding scheme, the encoder can do more than video compression. In this paper, a novel MPEG codec embedded with scene-effect information detection and insertion is proposed to provide more functionality at the decoder end. Based on the macroblock (MB) type of information that is generated simultaneously in the encoding process, a single-pass automatic scene-effect insertion MPEG coding scheme can be achieved. Using the USER/spl I.bar/DATA of picture header, the video output bitstreams by our method still conform to the conventional MPEG decoding system. The proposed method provides a solution toward upgrading the existing MPEG codec with low complexity to accomplish at least two major advantages. Precise and effective video browsing resulting from the scene-effect extraction can significantly reduce the user's time to look up what they are interested in. For video transmission, the bitstreams containing scene-effect information can obtain better error concealment performance when scene changes are involved. Compared with the gain it achieves, the payout of our algorithm is very worthy with comparatively small efforts.
A New Criterion for the Design of Variable Fractional-Delay FIR Digital Filters

Conventionally, variable fractional-delay finite-impulse-response digital filters are generally designed by minimizing the root-mean-square error of variable frequency response. In this paper, a new criterion concerning the minimization of the root-mean-square error of variable group-delay response is proposed. However, minimization is a highly nonlinear problem, so an iterative method is proposed in this paper to overcome it. To further reduce the maximum absolute group-delay error in the least squares design, an iterative weighting-updated technique is also proposed, which constitutes the outer loop of the overall iterative process while the iteration stated earlier makes up the inner loop. Several design examples will be presented to demonstrate the effectiveness of the proposed method.
Nighttime haze removal using color transfer pre-processing and Dark Channel Prior

Removing nighttime haze technique is an important and necessary procedure to avoid ill-condition visibility of human eyes. To increase the visibility of the scene, there are some existing methods for dehazing in the daytime. Specifically, these methods have a satisfactory dehazing quality in the daytime but most of them are not all successful in the nighttime. In this paper, the proposed method can be properly applied nighttime haze images even they have some ill-properties of low overall contrast, low overall brightness, and “blue shift” airlight color. The basic concept of proposed method is to use color transfer [7], refined Dark Channel Prior (DCP), and Bilateral Filter in Local Contrast Correction (BFLCC)[5]. Experimental results show that the proposed method has the reliable capabilities for removing nighttime haze and attractive for some applications such as computer vision, vehicle, aviation and national defense security.
Design of a class of time-constrained FIR digital filters by successive projections

Successive projection onto convex sets method is used to design a class of time-constrained finite impulse response (FIR) digital filters. This class includes Nyquist filters, partial-response FIR filters and Nth-band filter. This method is fast and very effective for filters with some time- and frequency-domain constraints, however the well-known Parks-McClellan filter design program is not suitable for designing these kinds of time-constrained FIR filters.
Fractional Fourier series expansion for finite signals and dual extension to discrete-time fractional Fourier transform

Conventional Fourier analysis has many schemes for different types of signals. They are Fourier transform (FT), Fourier series (FS), discrete-time Fourier transform (DTFT), and discrete Fourier transform (DFT). The goal of this article is to develop two absent schemes of fractional Fourier analysis methods. The proposed methods are fractional Fourier series (FRFS) and discrete-time fractional Fourier transform (DTFRFT), and they are the generalizations of Fourier series (FS) and discrete-time Fourier transform (DTFT), respectively.
Least mean p-power error criterion for adaptive FIR filter

An adaptive FIR filter based on the least mean p-power error (MPE) criterion is investigated. First, some useful properties of MPE function are studied. Three main results are as follows: 1) MPE function is a convex function of filter coefficients; so it has no local minima. 2) When input process and desired process are both Gaussian processes, then MPE function has the same optimum solution as the conventional Wiener solution for any p. 3) When input process and desired process are non-Gaussian processes, then MPE function may have better optimum solution than Wiener solution. Next, a least mean p-power (LMP) error adaptive algorithm is derived and some application examples are presented. Consequently, when the signal is corrupted by an impulsive noise, the adaptive algorithm with p=1 is preferred. Furthermore, when the signal is corrupted by noise or interference, the adaptive algorithm with proper choice of p may be preferred.
Complex adaptive IIR notch filter algorithm and its applications

In this paper, conventional real coefficient adaptive notch filters (ANF's) are extended to complex coefficient ones. This complex adaptive notch filter is implemented as a constrained IIR filter using a complex Gauss-Newton type algorithm to adjust its coefficients. When the ANF algorithm is applied to estimate the frequencies of sinusoids embedded in white noise. The results show that this algorithm has fast convergence, small bias, and achieves the Cramer-Rao bound. Furthermore, this ANF algorithm is used to estimate the parameters of multiple chirp signals. Simulation results also demonstrate very good performance. Finally, when this ANF algorithm is used to suppress narrowband interference in QPSK spread spectrum communication systems, the analytic result reveals that its signal-to-noise ratio improvement factor is grater than the factor of conventional one-sided prediction filter.
Signal Scaling by Centered Discrete Dilated Hermite Functions

We present a novel method to generate centered discrete dilated Hermite functions by utilizing Hermite-Gaussian differential equation and DFT commuting matrix proposed by Pei Compared with the conventional methods, our method provides much higher accuracy and wider working range. Based on expansion of compact support signals into discrete dilated Hermite basis, several examples of signal approximation and scaling are demonstrated. Our results in ECG signal compression can achieve lesser approximation error in comparison with discrete Daubechies wavelet transform. Also, our proposed discrete dilated Hermite functions have better ability to do signal scaling than the existing method.
Color invariant census transform for stereo matching algorithm

Illumination and color invariance are important problems in computer vision (CV). The Census transform (CT) can resist change of illumination intensity and is widely used for many applications in CV and consumer electronics. However, only grayscale images can be processed in the CT algorithm. In this paper, a new color Census transform (CCT) based on a color invariance model for stereo matching is proposed because color images are with more significant features and most source images are color. To evaluate the proposed method, its resulting disparity maps and computation time are compared with grayscale modified CT (MCT). Experimental results show that the computation time of the proposed method is little more than the grayscale MCT. But the proposed method is able to significantly improve structure features of disparity maps, compared to the grayscale MCT. Further, the CCT is not to be affected by shadows, highlights, and variations in illumination.
Analytical two-dimensional IIR notch filter design using outer product expansion

This work is concerned with the two-dimensional (2-D) digital notch filter design problem. First, the outer product expansion is used to reduce the 2-D notch filter design problem to two pairs of one-dimensional (1-D) filter design problems. Then, we develop a simple algebraic method for the design of two pairs of 1-D IIR filters. This approach not only has closed form transfer function but also satisfies bounded input/output (BIBO) stability condition. Finally, one example is included to illustrate the proposed design method, and the 2-D IIR notch filter is applied to eliminate the sinusoidal interference superimposed on an image.
A two-channel nonuniform perfect reconstruction filter Bank with irrational down-sampling factors

Most of the existing methods designed to implement fractional interpolation and decimation are limited by rational scaling factors such as L/M, where L and M are positive integers. The general procedure is usually done with up-sampling by L first, and then followed by down-sampling by M. This scheme, however, requires two steps and higher sampling rates to fulfill and is not capable in dealing with irrational scaling factors, which cannot be represented by L/M. We propose a new method to solve the above two difficulties by a single step. Furthermore, a new structure of a two-channel nonuniform perfect reconstruction filter bank is derived using this new method, and the experimental results are presented.
Fine-grain layered multicast based on hierarchical bandwidth inference congestion control

The paper presents an approach to facilitate bandwidth inference congestion (BIC) control in a fine-grain layered multicast for multimedia delivery. One-way delay trend detection has been shown to be effective in explicitly or implicitly estimating the end-to-end available bandwidth. By using a hierarchical layered probe in combination with the delay trend detection scheme, we propose a congestion control protocol for fine-grain layered multicast of 3D wavelet based scalable video streaming over heterogeneous networks.
Visual enhancement using sparsity-based image decomposition for low backlight displays

We propose a power-constrained image enhancement system to maintain human visual perception when the LCD or LED display is under low backlight. Adopting the low backlight mode can save the electricity and lengthen the battery using time. First, we deduce the relationship between the image and the backlight for maintaining the same visual perceptual quality. Then, we propose a sparsity-based image decomposition to separate the intensity image into base layer and detail layer. Afterwards, we refer to the image-backlight relationship to compensate the base layer, while we also adopt texture-aw are boosting to enhance the detail layer. Experimental simulated results show that our system outperforms than the compared systems.
Transform domain adaptive linear phase filter

Describes a new adaptive linear-phase filter whose weights are updated by the normalized least-mean-square (LMS) algorithm in the transform domain. This algorithm provides a faster convergence rate compared with the time domain linear phase LMS algorithm. Various real-valued orthogonal transforms are investigated such as the discrete cosine transform (DCT), discrete Hartley transform (DHT), and power of two (PO2) transform, etc. By using the symmetry property of the transform matrix, an efficient implementation structure is proposed. A system identification example is presented to demonstrate its performance.
Efficient fast design of three- and higher-dimensional FIR digital filters by analytical least squares method

An effective method is proposed for designing three- and higher-dimensional FIR digital filters in this paper. The method is based on deriving the closed-form matrix called by the inverse frequency response transformation matrix, such that the filter's coefficients can be computed directly from the given specifications without any iterative procedures and optimization techniques. Design examples are presented to demonstrate the flexibility and the efficiency of the method, and it is shown that even for filter lengths up to 21/spl times/21/spl times/21 only 0.4 s CPU time is needed.
Robust face detection for different chromatic illuminations

In this paper, we propose a robust face detection method in color images, and it is suitable for various faces and under different illuminations. The pre-processing is to convert the 3-D RGB color histogram into 2-D R-Y/B-Y color histogram and to introduce the concept of flesh tone. The second procedure is the kernel processing, which is 2-D color histogram normalization, to eliminate the: affine effect of the color histograms due to the illuminations changing. We propose the new standard flesh region by using statistics in the normalized domain, then extract the candidates of the flesh regions. And the post-processing is to use connected operators, some criterions and thresholds to obtain accurate face regions. Experimental results show that the face detection is successful and satisfactory for the synthetic images and the real images.
An efficient design of a variable fractional delay filter using a first-order differentiator

In this paper, the Taylor series expansion is used to transform the design problem of a fractional delay filter into the one of a first-order differentiator such that the conventional finite-impulse response and infinite-impulse response differentiators can be applied to design a fractional delay filter directly. The proposed structure is more efficient than the well-known Farrow structure in terms of filter coefficient storage because only one first-order differentiator needs to be designed and implemented. Moreover, one design example is demonstrated to illustrate the effectiveness of this new design approach.
Two-Dimensional Farrow Structure and the Design of Variable Fractional-Delay 2-D FIR Digital Filters

In this paper, a 2-D Farrow structure is proposed and used to implement variable fractional-delay (VFD) 2-D FIR digital filters. Compared with the existing literature, the desired response of a VFD 2-D digital filter is analyzed in detail, and it is found that there are four types of 2-D symmetric/antisymmetric sequences that need to be used for the design of VFD 2-D FIR digital filters. Moreover, due to the orthogonality among the approach functions, the four types of 2-D sequences can be determined independently, such that the dimension for each computation can be reduced drastically. For simplicity, only the designs of even-even- and odd-odd-order VFD 2-D filters are presented in this paper, and the other cases can be achieved in the same manner. To reveal the coefficient characteristics, the symmetric/antisymmetric properties of filter coefficients and the relationships between coefficients are all tabulated. Also, design examples such as nonseparable circularly symmetric low-pass VFD filters are presented to demonstrate the effectiveness of the proposed method.
Lagrange multiplier approach to the design of two-dimensional FIR digital filters for sampling structure conversion

The 1D Lagrange multiplier approach is extended for the design of 2D FIR digital filters with magnitude or derivative constraints. The method is based on minimizing the integrated square error for the frequency response over the passband and stopband while imposing magnitude or derivative constraints. The technique is used to design the interpolation and decimation filters for the sampling structure conversion. Numerical design examples are presented to demonstrate the effectiveness of the approach.
2-D FIR eigenfilters: a least-squares approach

The 1-D eigenfilter approach is extended to the design of 2-D FIR (finite-impulse-response) filters. By minimizing a quadratic measure of the error in the 2-D frequency band, an eigenvector of an appropriate matrix is computed to obtain the filter coefficients. The method is not only simple but also is optimal in the least-squares sense. Several numerical design examples for arbitrarily shaped 2-D filters are used to illustrate the effectiveness of the approach.
Improved design of digital 1-D and 2-D notch filters using general feedback structure

In this paper, a general feedback structure is proposed to improve the performance of existing digital notch filters. With the feedback structure, the notch filter can have a narrower stopband. This structure can be applied to any type of existing notch filter. We first derive the improved design of existing one-dimensional (1-D) filters. Then, by suitably extending the 1-D concept, the design of two-dimensional (2-D) notch filters is also derived. To demonstrate the effectiveness of the proposed design, an experiment on the interference removal of an image is presented. Moreover, a new forward and reverse algorithm for 2-D image filtering is proposed to reduce the transient error and enhance the signal-to-noise ratio drastically.
Complex notch filter design using allpass filter

Complex coefficient IIR notch filter design problems are investigated. The specification of a notch filter is first transformed into that of an allpass filter. An effective approach to the design of this desired allpass filter is developed. The realisation of the proposed notch filter is equivalent to the realisation of an allpass filter. Owing to the mirror-image symmetry relation between the numerator and denominator polynomials of allpass filters, the notch filter can be realised by a computationally efficient lattice structure with very low sensitivity.
On the coherent interference suppression using a spatially smoothing adaptive array

The behavior of a spatially smoothing adaptive array is examined. An expression for the weight vector is first derived. Using the array gain on the desired signal and the coherent interference is obtained. Then the expression for output signal-to-noise (SNR) is derived. It shows that the performance of the spatially smoothing array depends on the number of the subarrays, the angle separation, relative power and initial phase difference between the desired signal and the coherent interference. For good interference suppression it is found that the magnitude of the phase difference of the incident and interference signals must be greater than the beamwidths of both the subarray and the equivalent array. There is also a tradeoff between increasing the groups of subarrays and decreasing the number of elements in the subarrays. Computer simulation results are given that validate the analysis.
Fractional Bilinear Transform for Analog-to-Digital Conversion

In this correspondence, we propose a fractional bilinear transform used in analog-to-digital (A/D) conversion. This transfer function is derived by means of fractional delay filters. According to this transformation, first-order differentiator can be easily designed. Next, some design examples are illustrated to show the linear frequency mapping property when doing A/D conversion. Finally, the designed low-order digital differentiator is compared with the existing differentiators.