nils-herrmann/clean_scirepeval huggingface dataset:
New time-frequency distribution

Time-frequency distribution (TFD) is a tool to analyze time-varying signals. The cross term effect due to the second-order form of Cohen's class severely blocks its application. A new TFD is presented which not only meets several useful TFD requirements but also has good interference immunity. It is deduced that the role which this new TFD plays with respect to Levin's instantaneous power spectrum (IPS) is the counterpart of Choi-Williams exponential distribution (ED) with respect to the Wigner-Ville distribution (WVD).<<ETX>>
A joint design of dictionary approximation and maximum atom extraction for fast matching pursuit

We propose a new systematic approach to reduce matching pursuit (MP) encoder complexity. MP codecs are asymmetric as decoder complexity is low while the encoder complexity is extremely high. An MP encoder contains three components: the inner products, maximum atom extraction and atom encoding. We propose a new approach which combines the first two components using eigen-dictionary approximation and tree-based vector quantization (VQ). The advantages of this are a simpler design and a slower growth of computational costs as the target dictionary becomes large than traditional approaches. By varying the approximation accuracy, our algorithm can provide the trade-off between coding performance and speed-up of the MP encoder.
Design of a class of IIR eigenfilters with time- and frequency-domain constraints

An effective eigenfilter approach is presented to design special classes of infinite-impulse response (IIR) filters with time- and frequency-domain constraints is presented. By minimizing a quadratic measure of the error in the passband and stopband, an eigenvector of an appropriate real symmetric and positive-definite matrix is computed to get the filter coefficients. Several IIR filters such as notch filters, Nyquist filters and partial response filters can be easily designed by this approach. Some numerical design examples are illustrated to show the effectiveness of this approach.
Hybrid pyramid image coding and data compression

The authors discuss a hybrid pyramid coding scheme for image data compression that is based on two coding techniques: subband pyramid and Laplacian pyramid. Source data are first decomposed into seven bands by subband pyramid coding. Only the lowest band is further decomposed by the Laplacian pyramid technique to reduce correlations between pixels. The advantages of the hybrid pyramid scheme are its efficiency and compactness. In the coding process, each component is PCM coded. The computer simulation results show that the quality of the reconstructed image is good up to a compression ratio of 10:1.<<ETX>>
Design of discrete-time fractional Hilbert transformer

In this paper, the design problems of the fractional Hilbert transformer (FHT) are investigated. First, the conventional Hilbert transformer is generalized to FHT and its corresponding analytic signal is also defined to construct a single side-band (SSB) signal for saving communication bandwidth. Then, several methods are presented to design FIR and IIR fractional Hilbert transformers including a Hilbert transformer based method and an allpass filter based method. Finally, several design examples are presented to demonstrate the effectiveness of the proposed methods.
Pole–Zero Assignment of All-Pass-Based Notch Filters

In this brief, a new technique for designing the all-pass-based notch filter is proposed. An all-pass-based notch filter consists of an all-pass filter, which has the mirror-image symmetry relation between the numerator and denominator polynomials. With this property, a relationship between the pole angel and the zero angle of an all-pass-based notch filter is derived. Knowing this relationship, we can design an all-pass-based notch filter by assigning the pole position according to the zero position. The process of the new technique is illustrated in this brief. Moreover, experiments are presented to examine a track of the pole position at the specific frequency and to demonstrate a design example of an all-pass-based notch filter.
Auxiliary Metadata Delivery in View Synthesis Using Depth No Synthesis Error Model

In this paper, a novel data hiding scheme, 3D unseen visible watermarking (UVW) based on a depth no-synthesis-error (D-NOSE) model is proposed. The proposed method has the ability to detect and discover which region of a depth image is suitable for watermark embedding and calculate optimal variance in pixel values for watermarking. The watermark is embedded into the suitable region by modifying the depth map with optimal variation pixel values to ensure that the watermarked cover can be perceived the same as the original one with no synthesis error under normal rendering conditions. In the proposed UVW scheme, hidden information can be extracted successfully by the human visual system (HVS) when changing the rendering conditions. Experimental results prove that the proposed scheme has strong robustness and imperceptibility while depth distortions follow the thresholds derived from D-NOSE model. Practical applications and limitations of the proposed 3D UVW for auxiliary information delivery are also discussed in this paper.
Color image compression and limited display using self-organization Kohonen map

Several methods have been proposed to do color quantization for limited color displays. Self-organization of Kohonen feature maps (SOFM) is a very useful tool for data clustering. By extracting a special butterfly-jumping sequence from an image, a neural network was fed in that sequence of image data for SOFM training, and a fairly good color table was present to represent that image. The peak signal-to-noise ratio of the decoded image is high (about 35 dB in average for a 256 color image), and the perceptual quality is good as well, even with a small set of color tables (for example, 32 or 64 colors). Furthermore, the training process is fast. For encoding, we also propose an efficient algorithm based on the Kohonen map ordering property. By considering that the neighboring image pixels are closely related and by setting some acceptable thresholds, we can quickly get an encoded image. For further compression on the color indexed image with the limited color palette, we cut the indexed images into 4/spl times/4 blocks and send the block vectors into another SOFM neural network for training. Under the two-dimensional (2-D) mesh neural structure, SOFM vector quantization on an indexed image could largely reduce the color shift artifacts and avoid the requantization problem. About 0.5 b per pixel of coded image can be easily obtained with a fairly good perceptual quality. More importantly, the decoded color indexed images can be readily displayed. This will reduce the decoder complexity greatly.
Hiding multiple data in color images by histogram modification

We present a new histogram-based data-hiding algorithm that secret data is embedded in the least significant bit of the histogram value. To change the pixel value, it alters the histogram to accomplish data-hiding work. In the proposed algorithm, it is able to perform data hiding on the one-dimension histogram, two-dimension histogram map and three-dimension histogram cube. Besides, the multiple secret data hiding in various combinations of histogram spaces are successfully demonstrated in our experimental results. In addition, the natural and limited color images are tested in our experiments.
Content authentication of halftone video via flickering as sparse signal

We investigate the issue of content authentication for halftone videos transmitted over mobile devices. With an eye to the flickering that is the unique characteristic of halftone video and possesses the property of sparsity, a compressed sensing (CS)-based halftone video authentication method is presented. We show that the restricted isometry property (RIP) in CS can explain the principle of hash matching between two CS-based hashes. Promising results obtained from simulations demonstrate the feasibility of our method.
Effective wipe detection in MPEG compressed video using macro block type information

For video scene analysis, the wipe transition is considered most complex and difficult to detect. In this paper, an effective wipe detection method is proposed using the macroblock (MB) information of the MPEG compressed video. 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 of the area of the frame, the sequence will be considered a motionless wipe transition sequence. Besides, uncommon intracoded MB of the B frame can also be applied as an indicator of the motion 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. Easy extraction of MB type information, low-complexity analysis algorithm and robustness to arbitrary shape and direction of wipe transitions are the great advantages of the proposed method.
Facial makeup detection via selected gradient orientation of entropy information

This work presents a novel facial makeup detection method, which includes four steps: entropy information computation, feature extraction, feature selection and classification. To carry out this objective, first all face images are subject to the entropy information computation. Once the entropy images of faces are obtained, a feature extraction step is applied to the entropy images instead of original face images. The extracted features are further processed to reduce the redundant information on the feature vector, which is done by a feature selection procedure. A statistical analysis approach is chosen to realize this feature selection purpose, which aims to lower the feature dimension and maintain higher discrimination. In the last step, the makeup is detected by classifying faces into two groups: makeup and no-makeup. The experimental results on two databases indeed demonstrate the superiority of the proposed method.
A computer program for designing linear phase FIR digital filters by eigen-approach

A computer program for designing a large class of FIR linear-phase digital filters by eigen-approach is presented. The unique advantage of this approach over the McClellan-Parks algorithm is that it is general enough to incorporate both time- and frequency-domain constraints. This program not only can design standard bandpass filters, differentiators, and Hilbert transformers, but is also suitable for design of time-constrained FIR filters such as Nyquist filters, partial-response FIR filters, Mth-band filters, and higher-order differentiators. The simplicity and generality of this eigendesign algorithm make it useful for a wide variety of design applications.<<ETX>>
A new eigenfilter based on total least squares error criterion

In this paper, a new eigenfilter based on total least squares error criterion is investigated. The filter coefficients are obtained from the elements of the eigenvector corresponding to minimum eigenvalue of a real, symmetric and positive definite matrix. Four features of the new method are given. First, the computation of filter coefficients of the new eigenfilter is more numerically stable than that of the least-squares method whose solution is obtained by solving matrix inverse. Second, the new eigenfilter does not need a reference frequency point for normalization as done in traditional eigenfilter. Third, the solution of the new eigenfilter is closer to the solution of the least-squares method than that of the conventional eigenfilter. Fourth, the proposed method is easy to incorporate with linear constraints and can be extended to design equiripple and two dimensional linear phase filters. Several design examples are used to illustrate the effectiveness of this new design approach.
Design of 3-D FIR Cone-Shaped Filters by a Nest of McClellan Transformations

In this paper, the technique of a nest of McClellan transformations is proposed for the design of 3-D FIR cone- shaped filters. First, a transformation sub filter for fan-type mapping is found. Then the cosine term of a frequency variable of the above transformation sub filter is replaced by an embedded transformation sub filter which possesses circular contours. Several examples will be presented to demonstrate the effectiveness of the proposed method.
Color quantization by 3D spherical Fibonacci lattices

Color quantization is a technique that reduces the number of distinct colors for a color image. It usually maps pixels of the color image to a small color palette. The display quality of the color-quantized image is taken most seriously. But in practical applications, we also need to consider the complexity of quantization algorithm and the storage of parameters. We develop a 3D mathematic model to design the color palette such that the above things are solved. We will show the proposed scheme is computationally inexpensive and the display quality of the color-quantized image tends to perform better as the codebook size increases, but the storage of total parameters does not increase. In addition, we also prove the color-mapped images generated can be used for the edge detection of color image.
2.5-Domain Tri-Watermarking Algorithm for DCT-Based Video Protection

A 2.5-domain tri-watermarking algorithm (2.5D-TW) is presented in this paper. The proposed algorithm is the integration of dual domain bi-watermarking algorithm and visual cryptography, and the embedded tri-watermark is composed of three binary watermarks. The tri-watermark is embedded into the encoded blocks in discrete cosine transform (DCT) domain, however, the tri-watermark can be extracted from the DCT blocks and the decoded frames in spatial domain. Moreover, two types of third binary watermark of the tri-watermark are developed namely the intra-watermark and inter-watermark, those binary watermarks reveal the different robustness against various attacks. The proposed method attempts to localize the tampered areas and to detect the temporal attack.
Compressive Sensing Matrix Design for Fast Encoding and Decoding via Sparse FFT

Compressive sensing (CS) is proposed for signal sampling below the Nyquist rate based on the assumption that the signal is sparse in some transformed domain. Most sensing matrices (e.g., Gaussian random matrix) in CS, however, usually suffer from unfriendly hardware implementation, high computation cost, and huge memory storage. In this letter, we propose a deterministic sensing matrix for collecting measurements fed into sparse fast Fourier transform (sFFT) as the decoder. Compared with the conventional paradigm with Gaussian random matrix at encoder and convex programming or greedy method at decoders, sFFT can reconstruct sparse signals with very low computation cost under the comparable number of measurements. But, the limitation is that the signal must be sparse in the frequency domain. We further show how to relax this limitation into any domains with the transformation matrix or dictionary being circulant. Experimental and theoretical results validate that the proposed method achieves fast sensing, fast recovery, and low memory cost.
A moment-based approach for deskewing rotationally symmetric shapes

The covariance matrix of a rotationally symmetric shape is a scalar identity matrix. We apply this property of covariance matrix to deskew the skewed shape of rotational symmetry. The parameters of the deskew transformation matrix are solved by letting the covariance matrix of the transformed shape be equal to a scalar identity matrix. Then, the rotationally symmetric shape can be recovered by the deskew transformation matrix. The method does not rely on continuous contours, since only second-order moments of the input shape are required to be computed. Experimental results are also presented.
Detecting digital tampering by blur estimation

With powerful computer and mighty software, seasoned users could turn digital media into what they want. The detection of digital tampering has become a crucial problem. In most of the time, digital tampering is not perceptible by human: however, some traces of digital tampering may be left in the media during the process. Based on this idea, we present a method in this paper that could reveal blurred regions that indicate possible tampering without any embedded information such as watermarking technique. Effectiveness and results are presented, robustness is also discussed.
An Improved method for the design of variable fractional-delay IIR digital filters

In this paper, an improved method is proposed for the design of variable fractional-delay (VFD) IIR digital filters. The objective error function is constituted directly by the root-mean-squared error function of variable frequency response and the stability constrained function, so that the root-mean-squared error of variable frequency response can be minimized while the designed VFD IIR filter is stable. Several design examples will be presented to demonstrate the effectiveness of the proposed method.
Generating matrix of discrete Fourier transform eigenvectors

This paper provides a novel method to obtain the eigenvectors of discrete Fourier transform (DFT), which are accurate approximations to the continuous Hermite-Gaussian functions (HGFs). The proposed method uses a generating matrix and an initial eigenvector. By multiplying the initial eigenvector with the generating matrix, we can derive a new eigenvector. Repeating this procedure we can acquire all the eigenvectors. Compare with the conventional O(N3) commutative matrix method, this new method can generate all the DFT eigenvectors with complexity reduced to O(N2logN). The generating matrix can be further used to intensify the conventional commuting matrix. The simulation result shows that the Hermite-Gaussian like (HGL) eigenvectors of the strengthened commuting matrix outperform those of Santhanam's.
Design of FIR filters and allpass phase equalizers with prescribed magnitude and phase responses by two real Chebyshev approximations

It is noted that, since the coefficients of an FIR (finite impulse response) filter with arbitrary complex-valued desired frequency responses are neither symmetric nor antisymmetric, the Remez exchange algorithm cannot be applied directly. It is shown that the problem can be solved by dividing the original complex approximation into two real ones such that the Remex exchange algorithm can be applied by slightly modifying the Park-McClellan program. This method is much easier than the currently existing methods using linear programming and the performance is satisfied. More importantly, the overall complex errors are also equiripple in the complex Chebyshev sense. This approach has several practical advantages such as fast design time and easy implementation with comparable accuracy. Numerical design examples including a lowpass filter and sine-delay FIR allpass phase equalizers are given to show the effectiveness of this approach.<<ETX>>
Demosaicking of Color Filter Array patterns using Quaternion Fourier Transform and low pass filter

Recently, Color Filter Array (CFA) patterns are applied popularly in a digital camera. The CFA is a mosaic-like filter which only allows one primary color to be passed and captured by the sensor at each pixel, in order to save the cost. CFA will produce a mosaic-like color image and we have to use demosaicking algorithm to recover the original color image. In this paper, we propose a new method which uses Quaternion Fourier Transform (QFT) and low pass filter to do color image demosaicking. The proposed method is tested on several common CFA patterns and the efficacy of the proposed method is also demonstrated.
Design of complex coefficient variable fractional-delay allpass digital filters by eigenfilter approach

In this paper, the technique of eigenfilter approach is applied to the design of complex coefficient variable fractional-delay (VFD) allpass digital filters. The objective error function is formulated into a quadratic form aTQa where a is a coefficient vector and Q is a real, symmetric and positive-definite matrix. By Rayleigh principle, the eigenvector corresponding to the smallest eigenvalue of Q minimizes the error function, and is the desired solution. Several examples are presented to demonstrate the effectiveness of the proposed method.
Automatic text detection using multi-layer color quantization in complex color images

News, magazines, Web pages, etc. in modern life always contain much text information. In this paper, we propose a novel approach to detect text in images with very low false alarm rate. First of all, neural network color quantization is used to compact text color. Second, 3D histogram analysis chooses several color candidates, and then extracts each of these color candidates to obtain several bi-level images. Moreover, for each bi-level image, connectivity analysis and some morphological operators are fed to produce character candidates. Furthermore, we calculate some spatial features and relationships of each text candidate. Finally, we can localize text regions by authentication from LOG (Laplacian of Gaussian) edge detector. Meanwhile, in complex color images, multi-quantization layers can be integrated to reject non-text parts and reduce false alarm rate
Joint Bi-Watermarking and Halftoning Technique Capability for Both Tampered Areas Localization and Recovery of Still Image

This paper presents a method to localize and to recover the tampered areas in the watermarked image simultaneously. First, the proposed watermarking algorithm aims to embed a bi-watermark, which is the binary halftone of the downscaled host image, into the host image. While the watermarked image is tampered unauthorizedly, the extracted bi-watermark can be exploited to localize the tampered areas automatically without initial bi-watermark. Subsequently, Gaussian lowpass filter and quadratic programming are used to restore the bi-watermark to gray-scale image for inverse halftoning procedure. Eventually, the restored gray-scale image is used to recover the tampered areas.
Design of 3-D FIR Cone-Shaped Filters by McClellan Transformation and Least-Squares Contour Mapping

In this paper, the techniques of McClellan transformation and least-squares contour mapping are applied for the design of 3-D FIR cone-shaped filters directly. While it is difficult to find an unified set of constraints for the design of 3-D transformation sub filters with wide range of inclination degree, for example, two approaches are proposed and each of them can be used for cone-shaped filter design of a specified inclination range. Several examples will be presented to demonstrate the effectiveness of the proposed methods.
A comb filter design using fractional-sample delay

In this paper, a new comb filter design method using fractional sample delay is presented. First, the specification of the comb filter design is transformed into that of fractional delay filter design. Then, conventional finite impulse response (FIR) and allpass filter design techniques are directly applied to design fractional delay filter with transformed specification. Next, we develop a constrained fractional delay filter design approach to improve the performance of the direct design method. Finally, several design examples and an experiment of power line interference removal in an electrocardiogram (ECG) signal is demonstrated to illustrate the effectiveness of this new design approach.