nils-herrmann/clean_scirepeval huggingface dataset:
A unified approach to restoration, deinterlacing and resolution enhancement in decoding MPEG-2 video

The quality and spatial resolution of video can be improved by combining multiple pictures to form a single superresolution picture. We address the special problems associated with pictures of variable but somehow parameterized quality such as MPEG-decoded video. Our algorithm provides a unified approach to restoration, chrominance upsampling, deinterlacing, and resolution enhancement. A decoded MPEG-2 sequence for interlaced standard definition television (SDTV) in 4:2:0 is converted to: (1) improved quality interlaced SDTV in 4:2:0; (2) interlaced SDTV in 4:4:4; (3) progressive SDTV in 4:4:4; (4) interlaced high-definition TV (HDTV) in 4:2:0; (5) progressive HDTV in 4:2:0. These conversions also provide features such as freeze frame and zoom. The algorithm is mainly targeted at bit rates of 4-8 Mb/s. The algorithm is based on motion-compensated spatial upsampling from multiple images and decimation to the desired format. The processing involves an estimated quality of individual pixels based on MPEG image type and local quantization value. The mean-squared error (MSE) is reduced, compared to the directly decoded sequence, and annoying ringing artifacts, including mosquito noise, are effectively suppressed. The superresolution pictures obtained by the algorithm are of much higher visual quality and have lower MSE than superresolution pictures obtained by simple spatial interpolation.
Constellation Shaping for WDM Systems Using 256QAM/1024QAM With Probabilistic Optimization

In this paper, probabilistic shaping is numerically and experimentally investigated for increasing the transmission reach of wavelength division multiplexed (WDM) optical communication systems employing quadrature amplitude modulation (QAM). An optimized probability mass function (PMF) of the QAM symbols is first found from a modified Blahut-Arimoto algorithm for the optical channel. A turbo coded bit interleaved coded modulation system is then applied, which relies on many-to-one labeling to achieve the desired PMF, thereby achieving shaping gains. Pilot symbols at rate at most 2% are used for synchronization and equalization, making it possible to receive input constellations as large as 1024QAM. The system is evaluated experimentally on a 10 GBd, 5 channels WDM setup. The maximum system reach is increased w.r.t. standard 1024QAM by 20% at input data rate of 4.65 bits/symbol and up to 75% at 5.46 bits/symbol. It is shown that rate adaptation does not require changing of the modulation format. The performance of the proposed 1024QAM shaped system is validated on all 5 channels of the WDM signal for selected distances and rates. Finally, it is shown via EXIT charts and BER analysis that iterative demapping, while generally beneficial to the system, is not a requirement for achieving the shaping gain.
Tunable photonic RF generator for dynamic allocation and multicast of 1.25 Gbps channels in the 60 GHz unlicensed band

We propose an approach for dynamic channel allocation and multicast data delivery inside the 60 GHz unlicensed band. Channels, conveying 1.25 Gbps signals, can be allocated on demand by tuning the frequency sweep of an external cavity laser (ECL) either in the optical remote node (RN) or in the central office (CO). At the RN, we perform the replication of the original channel suitable for closely spaced multicast applications such as high definition (HD) video delivery where RN serves as a photonic radio frequency (RF) generator for both channel allocation and multicast. Experimental demonstration is presented with bit error rate (BER) performance below 10-9 for original and replicated channels after transmission through 22.8 km of standard single mode fiber (SSMF).
Optimal local dimming for LC image formation with controllable backlighting

Light emitting diode (LED)-backlit liquid crystal displays (LCDs) hold the promise of improving image quality while reducing the energy consumption with signal-dependent local dimming. However, most existing local dimming algorithms are mostly motivated by simple implementation, and they often lack concern for visual quality. To fully realize the potential of LED-backlit LCDs and reduce the artifacts that often occur in current systems, we propose a novel local dimming technique that can achieve the theoretical highest fidelity of intensity reproduction in either l1 or l2 metrics. Both the exact and fast approximate versions of the optimal local dimming algorithm are proposed. Simulation results demonstrate superior performances of the proposed algorithm in terms of visual quality and power consumption.
Virtual seminar room-modelling and experimentation in horizontal and vertical integration

The initial design considerations and research goals for an ATM network based virtual seminar room with five sites are presented. The basic observation behind the design of the virtual seminar room is, that besides the constant growth in available bandwidth for transmission in communication networks, many networks either already offer or are developing technologies to give quality of service (QoS) guarantees. This means that applications not only will support transmission of coded audio and video, but can be designed in a known and well-controlled network environment, which enables the applications to provide, in a broad sense, a high and reliable quality presented at the human computer interface.
Modeling the Subjective Quality of Highly Contrasted Videos Displayed on LCD With Local Backlight Dimming

Local backlight dimming is a technology aiming at both saving energy and improving visual quality on television sets. As the rendition of the image is specified locally, the numerical signal corresponding to the displayed image needs to be computed through a model of the display. This simulated signal can then be used as input to objective quality metrics. The focus of this paper is on determining which characteristics of locally backlit displays influence quality assessment. A subjective experiment assessing the quality of highly contrasted videos displayed with various local backlight-dimming algorithms is set up. Subjective results are then compared with both objective measures and objective quality metrics using different display models. The first analysis indicates that the most significant objective features are temporal variations, power consumption (probably representing leakage), and a contrast measure. The second analysis shows that modeling of leakage is necessary for objective quality assessment of sequences displayed with local backlight dimming.
Context Quantization by Minimum Adaptive Code Length

Context quantization is a technique to deal with the issue of context dilution in high-order conditional entropy coding. We investigate the problem of context quantizer design under the criterion of minimum adaptive code length. A property of such context quantizers is derived for binary symbols. A fast context quantizer design algorithm for conditioning binary symbols is presented and its complexity analyzed. It is conjectured that this algorithm is optimal. The context quantization is performed in what may be perceived as a probability simplex space rather than in the space of context instances.
Efficient depth map compression exploiting segmented color data

3D video representations usually associate to each view a depth map with the corresponding geometric information. Many compression schemes have been proposed for multi-view video and for depth data, but the exploitation of the correlation between the two representations to enhance compression performances is still an open research issue. This paper presents a novel compression scheme that exploits a segmentation of the color data to predict the shape of the different surfaces in the depth map. Then each segment is approximated with a parameterized plane. In case the approximation is sufficiently accurate for the target bit rate, the surface coefficients are compressed and transmitted. Otherwise, the region is coded using a standard H.264/AVC Intra coder. Experimental results show that the proposed scheme permits to outperformthe standardH.264/AVC Intra codec on depth data and can be effectively included into multi-view plus depth compression schemes.
Modeling Power-Constrained Optimal Backlight Dimming for Color Displays

In this paper, we present a framework for modeling color liquid crystal displays (LCDs) having local light-emitting diode (LED) backlight with dimming capability. The proposed framework includes critical aspects like leakage, clipping, light diffusion and human perception of luminance and allows adjustable penalization of power consumption. Based on the framework, we have designed a set of optimization-based backlight dimming algorithms providing a perceptual optimal balance of clipping and leakage, if necessary. The novel algorithms are compared with several other schemes known from the literature, using both objective measures and subjective assessment. The results show that the novel algorithms provide better quality at a given energy level or lower energy at a given quality level.
Simultaneous 60-GHz RoF Transmission of Lightwaves Emitted by ECL, DFB, and VCSEL

Simultaneous 60-GHz radio over fiber upconversion and fiber transmission of lightwaves produced by an external cavity laser, a distributed feedback laser, and a C-band vertical cavity surface emitting laser are demonstrated. The 1.25-Gb/s data are transmitted concurrently on each of the lightwaves attaining a bit error rate performance <10-9 level. Carrier suppression of 20 dB is achieved for all three lightwaves placed in a wide wavelength range. The 10-9 receiver sensitivity level for detection of three lightwaves falls in a <3-dB region. Reported close performance of the investigated techniques enables diversification of options for lightwave generation in millimeter-wave fiber-wireless networks.
Lossless, near-lossless, and refinement coding of bilevel images

We present general and unified algorithms for lossy/lossless coding of bilevel images. The compression is realized by applying arithmetic coding to conditional probabilities. As in the current JBIG standard the conditioning may be specified by a template. For better compression, the more general free tree may be used. Loss may be introduced in a preprocess on the encoding side to increase compression. The primary algorithm is a rate-distortion controlled greedy flipping of pixels. Though being general, the algorithms are primarily aimed at material containing half-toned images as a supplement to the specialized soft pattern matching techniques that work better for text. Template based refinement coding is applied for lossy-to-lossless refinement. Introducing only a small amount of loss in half-toned test images, compression is increased by up to a factor of four compared with JBIG. Lossy, lossless, and refinement decoding speed and lossless encoding speed are less than a factor of two slower than JBIG. The (de)coding method is proposed as part of JBIG2, an emerging international standard for lossless/lossy compression of bilevel images.
Maximizing entropy of pickard random fields for 2×2 binary constraints

This paper considers the problem of maximizing the entropy of two-dimensional (2D) Pickard Random Fields (PRF) subject to constraints. We consider binary Pickard Random Fields, which provides a 2D causal finite context model and use it to define stationary probabilities for 2×2 squares, thus allowing us to calculate the entropy of the field. All possible binary 2×2 constraints are considered and all constraints are categorized into groups according to their properties. For constraints which can be modeled by a PRF approach and with positive entropy, we characterize and provide statistics of the maximum PRF entropy. As examples, we consider the well known hard square constraint along with a few other constraints.
Improved virtual channel noise model for transform domain Wyner-Ziv video coding

Distributed Video Coding (DVC) has been proposed as a new video coding paradigm to deal with lossy source coding using side information to exploit the statistics at the decoder to reduce computational demands at the encoder. A virtual channel noise model is utilized at the decoder to estimate the noise distribution between the side information frame and the original frame. This is one of the most important aspects influencing the coding performance of DVC. Noise models with different granularity have been proposed. In this paper, an improved noise model for transform domain Wyner-Ziv video coding is proposed, which utilizes cross-band correlation to estimate the Laplacian parameters more accurately. Experimental results show that the proposed noise model can improve the Rate-Distortion (RD) performance.
Scalable-to-lossless transform domain distributed video coding

Distributed video coding (DVC) is a novel approach providing new features as low complexity encoding by mainly exploiting the source statistics at the decoder based on the availability of decoder side information. In this paper, scalable-to-lossless DVC is presented based on extending a lossy Transform Domain Wyner-Ziv (TDWZ) distributed video codec with feedback. The lossless coding is obtained by using a reversible integer DCT. Experimental results show that the performance of the proposed scalable-to-lossless TDWZ video codec can outperform alternatives based on the JPEG 2000 standard. The TDWZ codec provides frame by frame encoding. Comparing the lossless coding efficiency, the proposed scalable-to-lossless TDWZ video codec can save up to 5%-13% bits compared to JPEG LS and H.264 Intra frame lossless coding and do so as a scalable-to-lossless coding.
A Reconstruction Algorithm with Multiple Side Information for Distributed Compression of Sparse Sources

We consider the task of reconstructing target signals which are processed as sparse sources for a distributed compression scenario, where communication between the sources is prohibited, however, correlation of information among sources can be utilized at the decoder. We propose an efficient reconstruction algorithm with the aid of other given sources as multiple side information (SI) for such distributed sparse sources. The proposed algorithm takes advantage of both a compressive sensing (CS) reconstruction with SI and an iteratively weighted ℓ1-norm minimization by solving a general weighted multi-ℓ1 (or n-ℓ1) minimization. To utilize the known multiple SIs, the algorithm computes optimal weights on not only each individual SI but among SIs where the weights are adaptively updated according to changes at every iteration of the reconstruction. By this optimization, the proposed reconstruction algorithm with multiple SI (RAMSI) can robustly exploit the multiple SIs with different qualities. We experimentally demonstrate our algorithm on compressing feature histograms as sparse sources which are extracted from a multi-view image database for multi-view recognition. The results show that the RAMSI with multiple SIs efficiently outperforms the ℓ1 minimization and also the CS reconstruction with only one SI.
Maximum Mutual Information Vector Quantization of Log-Likelihood Ratios for Memory Efficient HARQ Implementations

Modern mobile telecommunication systems, such as 3GPP LTE, make use of Hybrid Automatic Repeat reQuest (HARQ) for efficient and reliable communication between base stationsand mobile terminals. To this purpose, marginal posterior probabilities of the received bits are stored in the form of log-likelihood ratios (LLR) in order to combine information sent across different transmissions due to requests. To mitigate the effects of ever-increasing data rates that call for larger HARQ memory, vector quantization (VQ) is investigated as a technique for temporary compression of LLRs on the terminal. A capacity analysis leads to using maximum mutual information (MMI) as optimality criterion and in turn Kullback-Leibler (KL) divergence as distortion measure. Simulations run based on an LTE-like system have proven that VQ can be implemented in a computationally simple way at low rates of 2-3 bits per LLR value without compromising the system throughput.
Multi-hypothesis distributed stereo video coding

Distributed Video Coding (DVC) is a video coding paradigm that exploits the source statistics at the decoder based on the availability of the Side Information (SI). Stereo sequences are constituted by two views to give the user an illusion of depth. In this paper, we present a DVC decoder for stereo sequences, exploiting an interpolated intra-view SI and two inter-view SIs. The quality of the SI has a major impact on the DVC Rate-Distortion (RD) performance. As the inter-view SIs individually present lower RD performance compared with the intra-view SI, we propose multi-hypothesis decoding for robust fusion and improved performance. Compared with a state-of-the-art single side information solution, the proposed DVC decoder improves the RD performance for all the chosen test sequences by up to 0.8 dB. The proposed multi-hypothesis decoder showed higher robustness compared with other fusion techniques.
Searching for the preferred backlight intensity in liquid crystal displays with local backlight dimming

Local backlight dimming is one of the most promising techniques for reducing power consumption and improving contrast characteristics of liquid crystal displays (LCD). In practice, due to light diffusion and a smaller number of backlight sources than pixels, local backlight dimming must often trade-off between leakage of light in dark pixels and clipping of luminance in bright pixels. Only few studies have analyzed the subjective preferences between different luminance and contrast levels. In this paper, we present a method for defining the perceptually optimal backlight level via subjective experimentation. As expected, the results show a clear correlation between image brightness and optimal backlight intensity; however, a large range of individual preferences was observed.
Entropy of Bit-Stuffing-Induced Measures for Two-Dimensional Checkerboard Constraints

A modified bit-stuffing scheme for two-dimensional (2-D) checkerboard constraints is introduced. The entropy of the scheme is determined based on a probability measure defined by the modified bit-stuffing. Entropy results of the scheme are given for 2-D constraints on a binary alphabet. The constraints considered are 2-D RLL(d,infin) for d=2,3 and 4 as well as for the constraint with a minimum 1-norm distance of 3 between 1s. For these results the entropy is within 1-2% of an upper bound on the capacity for the constraint. As a variation of the scheme, periodic merging arrays are also considered
Low-complexity compression of high dynamic range infrared images with JPEG compatibility

We propose a low-complexity High Dynamic Range (HDR) infrared image (IR) coding algorithm assuming the typical case of IR images with an active range of more than 8 bit depth, but less than 16 bit depth. First, we separate an input image into base and residual images with maximum 8 bit depth each. Then we compress each image by a JPEG baseline encoder and include the residual image bit stream into the application part of JPEG header of the base image. As a result, the base image can be reconstructed by JPEG baseline decoder. If the JPEG bit stream size of the residual image is higher than the raw data size, then we include the raw residual image instead. If the residual image contains only zero values or the quality factor for it is 0 then we do not include the residual image into the header. Experimental results show that compared with JPEG-XT Part 6 with ‘global Reinhard’ tone-mapping, the proposed approach has lower complexity and similar rate-distortion performance on IR test images.
Content layer progressive coding of digital maps

A new lossless context based method is presented for content progressive coding of limited bits/pixel images, such as maps, company logos, etc., common on the World Wide Web. Progressive encoding is achieved by encoding the image in content layers based on color level or other predefined information. Information from already coded layers are used when coding subsequent layers. This approach is combined with efficient template based context bilevel coding, context collapsing methods for multilevel images and arithmetic coding. Relative pixel patterns are used to collapse contexts. Expressions for calculating the resulting number of contexts are given. The new methods outperform existing schemes coding digital maps and in addition provide progressive coding. Compared to the state-of-the-art PWC coder, the compressed size is reduced to 50-70% on our layered map test images.
Feasibility Study and Experimental Verification of Simplified Fiber-Supported 60-GHz Picocell Mobile Backhaul Links

We propose and experimentally demonstrate a fiber-wireless transmission system for optimized delivery of 60-GHz radio frequency (RF) signals through picocell mobile backhaul connections. We identify advantages of 60-GHz links for utilization in short-range mobile backhaul through feasibility analysis and comparison with an alternative E-band (60-90 GHz) technology. The 60-GHz fiber-wireless-fiber setup is then introduced: two spans of up to 20 km of optical fiber are deployed and bridged by up to 4 m of wireless distance. The 60-GHz radio-over-fiber technology is utilized in the first span of fiber transmission. The system is simplified and tailored for delivery of on-off keying data signals by employing a single module for lightwave generation and modulation combined with a simplified RF downconversion technique by envelope detection. Data signals of 1.25 Gb/s are transmitted, and a bit-error-rate performance below the 7% overhead forward-error-correction limit is achieved for a range of potential fiber deployment scenarios. A spurious free dynamic range of 73 dB-Hz2/3 is attained for a frequency-doubling photonic RF upconversion technique. The power budget margin that is required to extend the wireless transmission distance from 4 m to a few hundred meters has been taken into account in the setup design, and the techniques to extend the wireless distance are analyzed.
Rate-adaptive constellation shaping for near-capacity achieving turbo coded BICM

In this paper the problem of constellation shaping is considered. Mapping functions are designed for a many-to-one signal shaping strategy, combined with a turbo coded Bit-interleaved Coded Modulation (BICM), based on symmetric Huffman codes with binary reflected Gray-like properties. An algorithm is derived for finding the Huffman code with such properties for a variety of alphabet sizes, and near-capacity performance is achieved for a wide SNR region by dynamically choosing the optimal code rate, constellation size and mapping function based on the operating SNR point and assuming perfect channel quality estimation. Gains of more than 1dB are observed for high SNR compared to conventional turbo coded BICM, and it is shown that the mapping functions designed here significantly outperform current state of the art Turbo-Trellis Coded Modulation and other existing constellation shaping methods.
Adaptive noise model for transform domain Wyner-Ziv video using clustering of DCT blocks

The noise model is one of the most important aspects influencing the coding performance of Distributed Video Coding. This paper proposes a novel noise model for Transform Domain Wyner-Ziv (TDWZ) video coding by using clustering of DCT blocks. The clustering algorithm takes advantage of the residual information of all frequency bands, iteratively classifies blocks into different categories and estimates the noise parameter in each category. The experimental results show that the coding performance of the proposed cluster level noise model is competitive with state-of-the-art coefficient level noise modelling. Furthermore, the proposed cluster level noise model is adaptively combined with a coefficient level noise model in this paper to robustly improve coding performance of TDWZ video codec up to 1.24 dB (by Bj⊘ntegaard metric) compared to the DISCOVER TDWZ video codec.