nils-herrmann/clean_scirepeval huggingface dataset:
JPEG-based perceptual image coding with block-based image quality metric

A JPEG-based perceptual image coder is proposed in this work, where a block-based image quality metric is used to optimize the rate-quality (RQ) performance. Under this framework, the quality of each image block is measured using a local quality metric while the overall image quality is evaluated by summing up all local quality metrics. A rate-quality optimization (RQO) problem is formulated in each macroblock of size 16×16 based on its associated empirical RQ curve. Then, to achieve the best perceptual image quality under a given bit budget constraint, the set of optimal quantization parameters (QPs) for image blocks is solved using the Lagrangian approach. It is demonstrated that the proposed perceptual image codec offers a significant improvement over the JPEG baseline in both subjective and objective evaluations.
Sparse Music Representation With Source-Specific Dictionaries and Its Application to Signal Separation

We propose a source-specific dictionary approach to efficient music representation, and apply it to separation of music signals that coexist with background noise such as speech or environmental sounds. The basic idea is to determine a set of elementary functions, called atoms, that efficiently capture music signal characteristics. There are three steps in the construction of a source-specific dictionary. First, we decompose basic components of musical signals (e.g., musical notes) into a set of source-independent atoms (i.e., Gabor atoms). Then, we prioritize these Gabor atoms according to their approximation capability to music signals of interest. Third, we use the prioritized Gabor atoms to synthesize new atoms to build a compact dictionary. The number of atoms needed to represent music signals using the source-specific dictionary is much less than that of the Gabor dictionary, resulting in a sparse music representation. For the single-channel music signal separation, we project the mixture signal onto source-specific atoms. Experimental results are given to demonstrate the efficiency and applications of the proposed approach.
Energy efficiency in data centers and cloud-based multimedia services: An overview and future directions

The expanding scale and density of data centers has made their power consumption an imperative issue. Data center energy management has become of unprecedented importance not only from an economic perspective but also for environment conservation. The recent surge in the popularity of cloud computing for providing rich multimedia services has further necessitated the need to consider energy consumption. Moreover, a recent phenomenon has been the astounding increase in multimedia data traffic over the Internet, which in turn is exerting a new burden on the energy resources. This paper provides a comprehensive overview of the techniques and approaches in the fields of energy efficiency for data centers and large-scale multimedia services. The paper also highlights important challenges in designing and maintaining green data centers and identifies some of the opportunities in offering green streaming service in cloud computing frameworks.
A DCT-Domain Video Alignment Technique for MPEG Sequences

An image/video registration technique for multiple compressed video inputs such as MPEG sequences is investigated. The proposed technique is based on the matching of discrete cosine transform (DCT) coefficients and motion vectors. First, the I frame of each input sequence is separated into the background and moving objects. For the background, coarse edge features are extracted by applying edge detectors of different characteristics to the luminance DC coefficients. Each detector generates a difference map for a single background. A threshold is determined for each difference map to produce a binary map. Then, alignment parameters are determined using the binary maps of input images generated by the same detector. For the moving object, alignment parameters can be finetuned by the motion information of all frames in the same group of pictures (GOP). Finally, the actual displacement in the pixel domain is estimated by the weighted average of alignment parameters from all background detectors and refinement parameters from motion information. It is shown by experimental results that the proposed method reduces the computational cost of image/video registration significantly in comparison with the traditional pixel domain registration techniques while achieving certain quality of composition
Automated multi-modality registration of 64-slice coronary CT angiography with myocardial perfusion spect

A multi-modality image registration algorithm for the alignment of myocardial perfusion SPECT (MPS) and coronary computed tomography angiography (CTA) scans is presented in this work. Coronary CTA and MPS provides clinically complementary information in the diagnosis of coronary artery disease. An automated registration algorithm is proposed utilizing segmentation results of MPS volumes, where regions of myocardium and blood pools are extracted and used as an anatomical mask. Using a variational framework, we adopt an energy functional with a piecewise constant image model and optimize it numerically with a gradient descent algorithm. The computational efficiency and robustness of the proposed automatic registration of CTA with MPS have been demonstrated by the experiments that yielded an average error smaller than a MPS voxel size.
Low-overhead error-resilient bit-plane image coding

An error resilient technique is proposed for bit-plane based image coding in this research. First, fast resynchronization is achieved with the suffix-rich Huffman code to minimize the length of error propagation. After regaining synchronization, the decoder may not align each symbol correctly due to the wrong number of previously decoded symbols in the error region. Thus, a scheme to identify probable locations of correctly decoded symbols is investigated so that these symbols can be shifted to their proper positions. This scheme exploits the correlation between decoded symbols of the current subband and their parent subband. It is demonstrated by experiments that the proposed error resilient technique results in a more robust codec with little sacrifice in coding efficiency.
Multiresolution image decomposition and compression using mathematical morphology

Multiresolution image decomposition based on linear filters has been widely used in image compression. In this research, we investigate a nonlinear multiresolution image decomposition based on mathematical morphology and obtain a morphological image pyramid. We propose to use opening and closing operations with a certain structure element to achieve image decomposition. The entropy and histogram of the difference images in the image pyramid are then examined. We use a numerical example to demonstrate that the morphological filtering approach provides some potential advantages over the conventional linear filtering approach in effective image coding.<<ETX>>
Noncoherent multiuser detection of DS-CDMA over multipath fading channels

The problem of joint channel estimation and multiple access interference suppression for an asynchronous code-division multiple-access system is studied. A low-complexity sliding-window scheme is proposed for channel tracking based on the expectation maximization (EM) algorithm and a noncoherent maximum a posteriori probability (MAP) multiuser detector. By exploiting the features of the discrete random phase ambiguities of channel estimates using the EM algorithm, the proposed scheme can track channel phase even if the channel is in a deep fade. In conjunction with iterative soft interference cancellation, the proposed detector can achieve a near single user system performance with polynomial complexity in the number of users.
H.264/SVC temporal bit allocation with dependent distortion model

The bit allocation problem for hierarchical B-pictures in H.264/SVC is studied with a GOP-based dependent distortion model in this work. Inter-dependency between temporal layers of H.264/SVC is often neglected because of the complexity involved, which often leads to poorer rate control performance. To address this shortcoming, we propose a distortion model that takes inter-dependency into consideration while preserving the low complexity of the encoding process. It is demonstrated by experimental results that the new distortion model results in a highly efficient bit allocation scheme, which outperforms the rate control algorithm in the JSVM 9.12 reference codec by a significant margin.
A common framework for blind multistage multiuser receivers of DS-CDMA in frequency-selective fading channels

The multistage (MS) Wiener filter proposed in J.S. Goldstein et al. (1998) is extended to blind maximum likelihood (ML) multiuser detection for direct-sequence (DS) code-division multiple access (CDMA) systems. This multistage ML detector is shown to share the same structure with the MS minimum-mean squared error (MMSE), minimum output energy (MOE) and best linear unbiased estimator (BLUE) filter banks (FBs) derived in S.-H. Wu et al. (2002) and S.-H. Wu et al. (2003), each with a distinctive output scaling matrix. Based on this result, a common framework is proposed for the implementation and analysis of coherent maximum ratio combining (MRC) and non-coherent differential equal gain combining (EGC) of these receivers. A generic bit error rate (BER) formula is provided for receivers constructed within this common framework. The BER floors for EGC receivers are analyzed and compared to those of the MRC schemes presented in S.-H. Wu et al. (2003). Based on simulation results, the heterogeneous EGC BLUE-ML receiver exhibits the best performance due to the fact that BLUE-FB is essentially the ML channel estimator and ML-FB is the ML symbol detector for the linear Gaussian system models of DS-CDMA systems.
Speech content authentication integrated with CELP speech decoders

A speech content authentication scheme, which is integrated with CELP speech coders to minimize the total computational cost is proposed in this research. Speech features relevant to semantic meaning are extracted, encrypted and attached as the header information. A low cost synchronization algorithm is used to resolve mis-synchronization caused by content preserving operations. Silent and tonal regions in the speech are identified with algorithms of low complexity to enhance the precision of integrity verification. This scheme is not only much faster than traditional cryptographic bitstream integrity algorithms, but also more compatible for a variety of applications. Experimental results are collected by using the GSM-AMR speech coder, and statistical analysis is performed to calculate the false positive rate of tamper detection.
A new initialization technique for VQ codebook design

The generalized Lloyd algorithm plays an important role in the design of vector quantizers (VQ) and in feature clustering for pattern recognition. In the VQ context, this algorithm provides a procedure to iteratively improve a codebook and results in a local minimum which minimizes the average distortion function. We propose an efficient method to obtain a good initial codebook that can accelerate the convergence of the generalized Lloyd algorithm, achieve a better local minimum and also result into lower entropy. Thus, it can achieve an overall better performance since the resulting rate-distortion pair is closer to the rate-distortion function of the input source.<<ETX>>
Enhanced Video Stream Switching Schemes for H.264

Two enhanced video stream switching schemes for H.264 are proposed aiming at prompt switching among compressed video streams coded at different quality levels and bit rates. The stream switching scheme using primary and secondary SP/SI pictures in H.264 is effective in switching, but degrades the compression efficiency of the transmitted stream even if the switching operation does not take place. In the two proposed schemes, no modification is made to the original compressed streams (namely, no primary SP picture is adopted) so that compression efficiency is maintained at switching points. As a result, switching points can be assigned flexibly in our enhanced schemes according to the need of applications and network conditions without worrying about the bit rate overhead. When switching occurs, the proposed schemes use a new picture type-DIFF (difference picture) in different ways to compensate the mismatch of reference frames. The first proposed scheme is designed to simplify the implementation while the second scheme is designed to further reduce the bit rate overhead. It is shown by experimental results that both of the proposed schemes outperform the switching scheme defined in H.264 and they are able to realize prompt stream switching without noticeable quality degradation and have a small bit rate overhead only when the actual switching operation occurs
Joint maximum likelihood estimation of carrier frequency offset and channel in uplink OFDMA systems

A maximum likelihood estimator (MLE) that jointly estimates the carrier frequency offset (CFO) and the channel response of each user in uplink OFDMA systems is investigated in this research. The proposed MLE distinguishes itself from existing methods by its applicability to more flexible carrier assignment schemes. It achieves high computational efficiency by transforming a multidimensional optimization problem into a one-dimensional optimization problem. A suboptimal method is developed to further reduce the computational complexity. It is demonstrated by simulation results that the proposed MLE can provide accurate CFO and channel estimation in both SISO and SIMO environments.
A hybrid BMC/OBMC motion compensation scheme

In this paper, we propose a hybrid scheme which incorporates the block motion compensation (BMC) scheme in the overlapped block motion compensation (OBMC) scheme. The main objective of this hybrid scheme is to improve a pure OBMC system with a lower motion bit rate and a lower search complexity while retaining about the same PSNR level. With this scheme, the encoder can determine the block mode under the tradeoff of complexity and visual quality. Furthermore, the motion bit rate can be reduced by smoothing the motion field of BMC blocks during motion search. Experimental results show that the complexity of both the encoder and the decoder is reduced while the visual quality remains as good as the pure OBMC system.
Audio Source Separation with Matching Pursuit and Content-Adaptive Dictionaries (MP-CAD)

A single-channel audio source separation algorithm based on the matching pursuit (MP) technique with content-adaptive dictionaries (CAD) is proposed in this work. The proposed MP-CAD algorithm uses content-dependent atoms that capture inherent characteristics of audio signals effectively. As compared with previous methods based on spectral decomposition and clustering in the time-frequency domain, the MP-CAD algorithm projects the time-domain audio signals onto a subspace spanned by content-adaptive atoms efficiently for their concise representation and separation. The effectiveness of the MP-CAD algorithm in audio signal approximation and single-channel source separation is demonstrated by computer simulation.
DCT-domain image registration techniques for compressed video

A technique for image registration in compressed video, such as motion JPEG or the I-picture of MPEG, is investigated. The technique is based on DCT (discrete cosine transform) coefficient matching. First, the coarse edge features are extracted by applying several edge detectors to luminance DC coefficients. Each detector generates one difference map for a single input image. A threshold is set up for each difference map to produce a binary map. Then, the alignment parameters are determined based on the binary maps of both input images generated by the same detector. Finally, the actual displacement in the pixel domain is calculated by averaging parameters from all detectors. Experimental results show that the proposed method reduces the computational cost of image registration dramatically as compared with the pixel domain and edge-based DCT domain registration techniques, while achieving a certain quality of composition.
Design of Collusion-Free Hiding Codes using MAI-Free Principle

A new methodology to design collusion-free hiding codes using the multi-access-interference-free (MAI-free) principle is proposed. A precoding technique was recently introduced in orthogonal frequency division multiplexing (OFDM) wireless communication systems to result in MAI-free codes, which simplifies the receiver design greatly. Being motivated by this work, we propose a new class of collusion-free codes called the OSIFT (orthogonal spreading followed by the inverse Fourier transform) codes. It is demonstrated by computer simulation that OSIFT codes have more robust performance against collusion attacks than existing collusion-free codes in an exemplary audio watermarking system.
Understanding and Removal of False Contour in HEVC Compressed Images

A contour-like artifact called false contour is often observed in large smooth areas of decoded images and video. Without loss of generality, we focus on detection and removal of false contours resulting from the state-of-the-art High Efficiency Video Coding codec. First, we identify the cause of false contours by explaining the human perceptual experiences on them with specific experiments. Next, we propose a precise pixel-based false contour detection method based on the evolution of a false contour candidate (FCC) map. The number of points in the FCC map becomes fewer by imposing more constraints step by step. Special attention is paid to separating false contours from real contours such as edges and textures in the video source. Then, a decontour method is designed to remove false contours in the exact contour position while preserving edge/texture details. Extensive experimental results are provided to demonstrate the superior performance of the proposed false contour detection and removal method in both compressed images and videos.
A Graph-Based Approach to Multi-Cell OFDMA Downlink Resource Allocation

A novel, practical and low-complexity multi-cell OFDMA downlink channel assignment method using a graph- based approach is proposed in this work. The inter-cell interference (ICI) information is obtained through inference from the diversity set of mobile stations (MSs) and presented in the form of an interference graph. The proposed downlink channel assignment method consists of two phases. The task of ICI reduction is mapped to the MAX fe-CUT problem in graph theory and solved in the first phase. Then, channel assignment is conducted by taking into account instantaneous channel conditions in the second phase. State-of-the-art ICI management techniques such as ICI coordination (ICIC) and base station cooperation (BSC) are incorporated in our framework. Heuristic algorithms are proposed to solve both phases of the problem efficiently. Simulation is conducted to demonstrate the effectiveness of the proposed solution, where the SINR improvement can be as high as 4.5 dB. The proposed solution can be used in next generation cellular systems such as 3 GPP long term evolution (LTE) and IEEE 802.16 m.
Distributed edge sensor detection with one- and two-level decisions

A statistical approach to distributed edge sensor detection is proposed for wireless sensor networks. Edge sensor detection is a technique to decide whether a target sensor is an edge sensor and is based on data from its neighboring sensors. It is desirable that the computational complexity be low and the amount of data transferred among sensors be small. With some reasonable assumptions and the maximal likelihood technique, we propose both one-level and two-level decision methods to fulfil the above two constraints.
Analysis of multistage linear parallel interference cancellation in CDMA systems using graphical representation

The bit error probability of the multistage linear parallel interference canceller in a long-code code division multiple access (CDMA) system is analyzed with a graphic approach in this research. The decision statistic is modelled as a Gaussian random variable, whose mean and variance can be expressed as functions of moments of (R-I), where R is the correlation matrix of the signature sequences. Since the complexity of calculating these moments increases rapidly with the growth of the stage index, a graphical representation of moments is developed to facilitate the computation. Propositions are presented to relate the moment calculation problem to several well known problems in graph theory, i.e., the coloring, the graph decomposition, the biconnected component, and the Euler tour problems. It is shown that the analytic results of the bit error probability match well with simulation results.
Artifact reduction for JPEG-compressed images with VQ and linear estimation

A new non-iterative algorithm to remove compression artifacts appearing in JPEG encoded images is proposed in this work. Since degradation caused by the transform and the quantization is difficult to describe mathematically, a clustering technique is used to analyze the statistics of the source and noise in the training. Then, coefficients of a linear prediction filter are pre-calculated and stored in a codebook. In the decoding stage, the linear filter with proper coefficients is applied to quantized transform coefficients and to pixels at block boundaries after the inverse DCT. Experimental results show that the proposed method can efficiently reduce coding artifacts with a low computational complexity.
Reduced-rank space-time channel estimation for DS-CDMA in MIMO dispersive channels

A reduced-rank space-time channel estimation scheme is presented for uplink multiuser DS-CDMA (direct-sequence code-division multiple access) systems in dispersive MIMO (multiple input and multiple output) channels. The proposed method is based on the alternative power (AP) method with the aid of pilot symbols. It is shown that the mean squared error (MSE) of channel estimation can be improved via rank order selection where optimal performance can be achieved using the generalized likelihood ratio test (GLRT). Both analytical and simulated results are provided to demonstrate the performance of the proposed scheme with various measurement criteria.
Impact of heterogeneous deployment on lifetime sensing coverage in sensor networks

While most research on wireless sensor networks have focused on the deployment of large numbers of cheap homogeneous sensor devices, in practical settings, it is often feasible to consider heterogeneous deployments of devices with different capabilities. Under the prescribed cost constraints, we analyze such heterogeneous deployments both mathematically and through simulations, and show how they impact the coverage aging process of a sensor network, i.e., how it degrades over time as some nodes become energy-depleted. We derive expressions for the heterogeneous mixture of devices that optimizes the lifetime sensing coverage in a single-hop direct communication model. We then investigate a multi-hop communication model through simulations, and examine the impact of heterogeneity on lifetime sensing coverage and coverage aging both with and without data aggregation. Our results show that using an optimal mixture of many inexpensive low-capability devices and some expensive high-capability devices can significantly extend the duration of a network's sensing performance.