nils-herrmann/clean_scirepeval huggingface dataset:
Relationships among digital one/half band filters, low/high order differentiators and discrete/differentiating Hilbert transformers

It is shown that there exists a close relationship among digital one/half band filters, low/high order differentiators, and discrete/differentiating Hilbert transformers. An attempt is made to present a complete picture of their interrelationships and conversions between one another. A table and some block diagrams have been developed for their impulse response connections, and a design example is also given for illustration.<<ETX>>
Efficient MPEG Compressed Video Analysis Using Macroblock Type Information

Efficient indexing methods are required to handle the rapidly increasing amount of visual information within video databases. Video analysis that partitions the video into clips or extracts interesting frames is an important preprocessing step for video indexing. We develop a novel method for video analysis using the macroblock (MB) type information of MPEG compressed video bitstreams. This method exploits the comparison operations performed in the motion estimation procedure, which results in specific characteristics of the MB type information when scene changes occur or some special effects are applied. Only a simple analysis on MB types of frames is needed to achieve very fast scene change, gradual transition, flashlight, and caption detection. The advantages of this novel approach are its direct extraction from the MPEG bitstreams after VLC decoding, very low complexity analysis, frame-based detection accuracy and high sensitivity.
Video Halftoning Preserving Temporal Consistency

Video halftoning is a key technology for use in the new display device, electronic paper (e-paper). This is still a rather unexplored field. The challenging issue of video halftoning is the elimination of flicker flaw that will appear due to error diffusion in the temporal domain. In this paper, we propose a new video halftoning method, which is composed of spatial error diffusion and inter-frame reference error diffusion. In addition, since our method can efficiently reduce the flicker flaws, another advantage is that the halftone video sequence can be efficiently compressed. When compared with traditional 2D and 3D error diffusion techniques, experimental results show that our method can significantly reduce the average flicker rates.
Improved SVD-Based Watermarking for Digital Images

Digital watermark is used to prove the rightful ownership or protect a customer's right of using the medium. Liu et al. proposed a SVD-based watermarking scheme, but their method has a serious defect; for un-watermarked images it still incorrectly extracts out the watermark. In this paper, we propose an improved SVD-based watermarking method to resolve this defect. We will show our method is successful in resolving rightful ownership of watermarked image with good accuracy, good robustness and good imperceptibility.
3D spatiotemporal subband decomposition of image sequences by mathematical morphology

An efficient 3D spatiotemporal image sequence decomposition method using mathematical morphology is described. It decomposes the input signal spectrum into eight spatiotemporal subband images by using two different sets of structuring elements. Each band image can be decimated and coded effectively for data transmission. This subband pyramid scheme preserves the number of pixels as in the original image, has an efficient hierarchical data structure, and also allows parallel implementation. The unique advantages of morphology over the linear filtering approach are its direct geometric interpretation, simplicity, and efficiency in parallel/pipelining hardware implementation. Some image sequence examples are given to show the effectiveness of this approach.<<ETX>>
The discrete fractional cosine and sine transforms

This paper is concerned with the definitions of the discrete fractional cosine transform (DFRCT) and the discrete fractional sine transform (DFRST). The definitions of DFRCT and DFRST are based on the eigen decomposition of DCT and DST kernels. This is the same idea as that of the discrete fractional Fourier transform (DFRFT); the eigenvalue and eigenvector relationships between the DFRCT, DFRST, and DFRFT can be established. The computations of DFRFT for even or odd signals can be planted into the half-size DFRCT and DFRST calculations. This will reduce the computational load of the DFRFT by about one half.
Motion-based grouping of optical flow fields: the extrapolation and subtraction technique

The goal of three-dimensional (3-D) motion segmentation is to identify the image areas projected by different moving objects in 3-D space. However, many prevailing methods merely detected the discontinuity of optical flow field and usually considered these boundaries as that produced by different 3-D motions. In fact, the flow discontinuity can be generated either by two different 3-D motions or by the structural discontinuity on the same moving object. The wrong identification causes several problems in 3-D motion estimation. A simple method called the extrapolation and subtraction (ES) technique is proposed to solve these problems. The input image flow field is first partitioned into several functionally analytic regions. Each analytic region is assumed to be projected by a roughly planar patch moving in 3-D space. Based on the parameterization of these analytic flow fields, the ES technique provides a very simple and fast method to test the 3-D motion compatibility between two interested analytic flow fields.
An introduction to discrete finite frames

The frame concept was first introduced by Duffin and Schaeffer (1952), and it is widely used today to describe the behavior of vectors for signal representation. The Gabor (1946) expansion and wavelet transform are two special well-known cases. The goal of this article is to describe the frame theory and introduce a simple tutorial method to find discrete finite frame operators and their frame bounds. An easily implementable method for finding the discrete finite frame and subframe operators has been presented by Kaiser (1994). We introduce the method of Kaiser to compute the discrete finite frame operator. Using subframe operators, the biorthogonal basis and projection vectors in a subspace can be easily calculated. Gabor and wavelet analysis are two popular tools for signal processing, and they can reveal time-frequency distribution for a nonstationary signal. Both schemes can be regarded as signal decompositions onto a set of basis functions, and their basis functions are derived from a single prototype function through simple operations. Therefore, the basis functions used in Gabor and wavelet analysis can be regarded as special frames. For completeness we also make some simple introductions on the results of special frames such as discrete Gabor and wavelet analysis.
A weighted least-squares method for the design of stable 1-D and 2-D IIR digital filters

We present a new approach to the least-squares design of stable infinite impulse response (IIR) digital filters. The design is accomplished by using an iterative scheme in which the denominator polynomial obtained from the preceding iteration is treated as a part of the weighting function, and each iteration is carried out by solving a standard quadratic programming problem that yields a stable rational function. When the iteration converges, a stable and truly least-squares solution is obtained. The method is then extended to address the least-squares design of stable IIR two-dimensional (2-D) filters. Examples are included to illustrate the proposed design techniques.
Minimum-phase FIR filter design using real cepstrum

The real cepstrum is used to design an arbitrary length minimum-phase FIR filter from a mixed-phase sequence. There is no need to start with the odd-length equiripple linear-phase sequence first. Neither phase-unwrapping nor root-finding is needed. Only two FFTs and an iterative procedure are required to compute the filter impulse response from real cepstrum; the resulting magnitude response is exactly the same with the original sequence.
Discrete fractional Fourier transform based on orthogonal projections

The continuous fractional Fourier transform (FRFT) performs a spectrum rotation of signal in the time-frequency plane, and it becomes an important tool for time-varying signal analysis. A discrete fractional Fourier transform has been developed by Santhanam and McClellan (see ibid., vol.42, p.994-98, 1996) but its results do not match those of the corresponding continuous fractional Fourier transforms. We propose a new discrete fractional Fourier transform (DFRFT). The new DFRFT has DFT Hermite eigenvectors and retains the eigenvalue-eigenfunction relation as a continous FRFT. To obtain DFT Hermite eigenvectors, two orthogonal projection methods are introduced. Thus, the new DFRFT will provide similar transform and rotational properties as those of continuous fractional Fourier transforms. Moreover, the relationship between FRFT and the proposed DFRFT has been established in the same way as the conventional DFT-to-continuous-Fourier transform.
Modified spatial smoothing for coherent jammer suppression without signal cancellation

An adaptive array processor is presented for suppressing coherent jammers. It performs spatial smoothing, after removing the desired signal, to adapt a weight vector, which is then copied to a slave beamformer to eliminate jammers. This processor can avoid signal cancellation occurring in performing spatial smoothing with the desired signal present. Nulls generated by the processor in directions of coherent jammers are much deeper than those generated by performing spatial smoothing with the desired signal present.
Minimax Design of Variable Fractional-Delay FIR Digital Filters by Iterative Weighted Least-Squares Approach

In this letter, an iterative weighted least-squares (LS) approach is proposed for the design of variable fractional-delay (VFD) finite impulse response (FIR) digital filters in minimax sense. For deriving the elements of relevant matrices, there is no need for numerical integration or closed-form formulation and they obey given specifications. Comparing with the existing method, the proposed method does not lead to a misleading problem, and the performance of convergence is also better. Especially, it is found that the used LS weighting function is only dependent on the frequency, not on the tunable parameter, which makes it easier for the minimax design of VFD FIR digital filters.
Spatial Affine transformations of images by using fractional shift fourier transform

Affine transformations of images are common used in modern signal processing, image processing, and computer graphics areas. Take rotation of images for example, we have to calculate the positions of pixels after rotation and use methods like cubic, bilinear, and nearest neighbor interpolation to interpolate some pixels in between. These interpolation and spatial-domain-based methods are slow, cumbersome and the PSNR (Peak signal to noise ratio) is also not satisfactory. In this paper, we propose frequency domain based method for Affine transformations by applying proposed fractional shift Fourier transform and modified inverse Fourier transform. For rotation of gray-scale images, three shearing matrices and fractional shift Fourier transform are applied to complete the task. Fast Fourier transform (FFT) algorithm can be used to implement Fourier transform and therefore our method is very fast and precise. For the general case, i.e. Affine transformations, we combine shearing matrices, fractional shift Fourier transform and Modified inverse Fourier transform method to achieve arbitrary Affine transformations with small distortion (above 50dB PSNR).
Efficient and effective wipe detection in MPEG compressed video based on the macroblock information

We propose an effective and efficient wipe detection method based on the macroblock information of the MPEG compressed video. Two types of wipe transitions are taken into consideration. By analyzing the prediction directions of B frames, which are revealed in the MB types, the scene change region of each frame can be found. Once the accumulation of the scene change regions covers most area of the frame, the sequence will be considered a wipe transition sequence. Besides, uncommon intra-coded MBs of the B frame can also be applied as an indicator of the wipe transition. A very simple analysis based on small amount of MB type information is sufficient to achieve wipe detection directly on MPEG compressed video.
Odd Ramanujan Sums of Complex Roots of Unity

A special class of odd-symmetric length-4N periodic signals is studied, and it is shown how the odd Ramanujan sums are used as weighting coefficients to compute their pure imaginary discrete Fourier transform (DFT) integer-valued coefficients. The odd Ramanujan sum, being the sums of complex roots of unity, can be calculated either using closed-form formulas or computed recursively through the impulse response of a derived infinite impulse response (IIR) filter. This special class of odd-symmetric signals and odd Ramanujan sums can be combined together with the previous even-symmetric special class signals and the well-known even Ramanujan sums as a useful tool for signal processing
Secure and robust sift with resistance to chosen-plaintext attack

Scale-invariant feature transform (SIFT) is a powerful tool extensively used in the community of pattern recognition and computer vision. The security issue of SIFT, however, is relatively unexplored. We point out the potential weakness of SIFT, meaning that the SIFT features can be deleted or destroyed while maintaining acceptable visual qualities. To properly achieve the tradeoff between security and robustness of SIFT, we present a cube-based secure transformation mechanism to enable the SIFT method to resist up to the chosen plaintext attack while robustness against geometric attacks can still be maintained. Security analysis and robustness verification are provided to demonstrate the effectiveness of the proposed (and modified) SIFT method.
Algebraic identification for optimal nonorthogonality 4×4 complex space-time block codes using tensor product on quaternions

The design potential of using quaternionic numbers to identify a 4/spl times/4 real orthogonal space-time block code has been exploited in various communication articles. Although it has been shown that orthogonal codes in full-rate exist only for 2 Tx-antennas in complex constellations, a series of complex quasi-orthogonal codes for 4 Tx-antennas is still proposed to have good performance recently. This quasi-orthogonal scheme enables the codes to reach the optimal nonorthogonality, which can be measured by taking the expectation over all transmit signals of the ratios between the powers of the off-diagonal and diagonal components. This correspondence extends the quaternionic identification to the above encoding methods. Based upon tensor product for giving the quaternionic space a linear extension, a complete necessary and sufficient condition for identifying any given complex quasi-orthogonal code with the extended space is generalized by considering every possible two-dimensional R-algebra.
Direct N-point DCT computation from three adjacent N/3-point DCT coefficients

An efficient method for computing a length-N Discrete Cosine Transform (DCT) from three consecutive length-N/3 DCTs is proposed. This method differs from previous ones in that it reduces considerable 31-38% 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 block DCT-based image by the factor of 1/2/sup /spl alpha//3/sup /spl beta//. This would be very useful in high-definition television (HDTV) standard, whose display size is usually 16:9. The comparison with conventional methods is provided.
A parallel decoding algorithm for IFS codes without transient behavior

Iterated function systems (IFSs) have received great attention in encoding and decoding fractal images. Barnsley (1988) has shown that IFSs for image compression can achieve a very high compression ratio for a single image. However, the major drawback of such a technique is the large computation load required to both encode and decode a fractal image. We provide a novel algorithm to decode IFS codes. The main features of this algorithm are that it is very suitable for parallel implementation and has no transient behavior. Also, from the decoding process of this method we can understand the encoding procedure explicitly. One example is illustrated to demonstrate the quality of its performance.
STFT With Adaptive Window Width Based on the Chirp Rate

An adaptive time-frequency representation (TFR) with higher energy concentration usually requires higher complexity. Recently, a low-complexity adaptive short-time Fourier transform (ASTFT) based on the chirp rate has been proposed. To enhance the performance, this method is substantially modified in this paper: i) because the wavelet transform used for instantaneous frequency (IF) estimation is not signal-dependent, a low-complexity ASTFT based on a novel concentration measure is addressed; ii) in order to increase robustness to IF estimation error, the principal component analysis (PCA) replaces the difference operator for calculating the chirp rate; and iii) a more robust Gaussian kernel with time-frequency-varying window width is proposed. Simulation results show that our method has higher energy concentration than the other ASTFTs, especially for multicomponent signals and nonlinear FM signals. Also, for IF estimation, our method is superior to many other adaptive TFRs in low signal-to-noise ratio (SNR) environments.
Distributed compressive sensing: Performance analysis with diverse signal ensembles

Distributed compressive sensing is a framework considering jointly sparsity within signal ensembles along with multiple measurement vectors (MMVs). The current theoretical bound of performance for MMVs, however, is derived to be the same with that for single MV (SMV) because the characteristics of signal ensembles are ignored. In this work, we introduce a new factor called "Euclidean distances between signals" for the performance analysis of a deterministic signal model under MMVs framework. We show that, by taking the size of signal ensembles into consideration, MMVs indeed exhibit better performance than SMV. Although our concept can be broadly applied to CS algorithms with MMVs, the case study conducted on a well-known greedy solver, called simultaneous orthogonal matching pursuit (SOMP), will be explored in this paper. We show that the performance of SOMP, when incorporated with our concept by modifying the steps of support detection and signal estimations, will be improved remarkably, especially when the Euclidean distances between signals are short. The performance of modified SOMP is verified to meet our theoretical prediction.
A novel block truncation coding of color images using a quaternion-moment-preserving principle

Block truncation coding (BTC) is an efficient tool for image compression. To compress color-pixel blocks, a novel color BTC algorithm, called quaternion-moment block truncation coding (QMBTC), is presented. Analytical formulas for QMBTC, whose computation time is on the order of pixel block size, are derived by using quaternion arithmetic and the moment-preserving principle. The proposed color BTC algorithm can adaptively truncate a pixel block into one or two output classes according to the distribution of the color values inside the blocks. The experimental results show that the compression ratio is increased as compared with existing color BTC algorithms, and the picture quality of the reconstructed images is satisfactory. In addition, a post-BTC data compression scheme is proposed to further compress the subimage constructed by reproduction colors of truncated pixel blocks. Using a lookup table to display decoded data, this postprocessing scheme can output images acceptable to human eyes.
Design of Allpass Fractional Delay Filter and Fractional Hilbert Transformer Using Closed-Form of Cepstral Coefficients

The paper describes a cepstrum-based approach to design the maximally flat allpass fractional delay filter and the fractional Hilbert transformers. The maximal flatness criteria on the phase/group delay responses are formulated as a system of linear equations in terms of cepstral coefficients. The solution to the cepstral coefficients has closed-form expression. Moreover, it's very attractive that the resultant cepstral coefficients are directly proportional to the design parameters: the fractional delay and phase shift in the delay filters and Hilbert transformers, respectively. This virtue implies a simple scheme for updating new filter coefficients corresponding to various delay value or phase shift amount. Only one set of cepstral coefficients needs to be designed and stored and the new set is obtained simply by multiplying the old set with a ratio. A fixed module is used to update the filter coefficients from the cepstral coefficients.
Design of 1-D and 2-D IIR eigenfilters

An effective method is proposed for the design of recursive digital filters in the time/spatial domain. The method is based on the computation of an eigenvalue and its corresponding eigenvector of an appropriate real symmetric and positive-definite matrix derived from the objective error function of the impulse response in the least-squares sense. The method can be used to design 1D IIR digital filters as well as 2D IIR digital filters. The method is easy and the performance is comparable to those of the existing methods. One of the main advantages of the proposed method is that the solution is obtained directly without the need for iteration.
Closed-form design of maximally flat FIR fractional delay filters

Eight types of maximally flat finite impulse response (FIR) fractional delay filters are proposed. They are designed by separately approximating the real part and the imaginary part of the frequency response. Among these eight types of filters, two of them are equivalent to the existing design results in the open literature. Therefore, a more general closed-form design of the maximally flat FIR fractional delay filters is described in this letter, and some design examples of FIR fractional delay filters will be illustrated
Spatially-varying out-of-focus image deblurring with L1-2 optimization and a guided blur map

In this paper, we propose a spatially-varying deblurring method to remove the out-of-focus blur. Our proposed method mainly contains three parts: blur map generation, image deblurring, and scale selection. First, we derive a blur map using local contrast prior and the guided filter. Second, we propose our image deblurring method with L1-2 optimization to obtain a better image quality. Finally, we adopt the scale selection to ensure our output free from ringing artifacts. The experimental results demonstrate our proposed method is promising.
Optimal Discrete Gaussian Function: The Closed-Form Functions Satisfying Tao’s and Donoho’s Uncertainty Principle With Nyquist Bandwidth

In this paper, closed-form discrete Gaussian functions are proposed. The first property of these functions is that their discrete Fourier transforms are still discrete Gaussian functions with different index parameter. This index parameter, which is an analogy to the variance in continuous Gaussian functions, controls the width of the function shape. Second, the discrete Gaussian functions are positive and bell-shaped. More important, they also have finite support and consecutive zeros. Thus, they satisfy Tao's and Donoho's uncertainty principle of discrete signal. The construction of these discrete Gaussian functions is inspired by Kong's zeroth-order discrete Hermite Gaussian functions. Three examples are discussed.