nils-herrmann/clean_scirepeval huggingface dataset:
Data compression of scanned halftone images

A new method for coding scanned halftone images is proposed. It is information-lossy, but still preserving the image quality, compression rates of 16-35 have been achieved for a typical test image scanned on a high resolution scanner. The bi-level halftone images are filtered, in phase with the halftone grid, and converted to a gray level representation. A new digital description of (halftone) grids has been developed for this purpose. The gray level values are coded according to a scheme based on states derived from a segmentation of gray values. To enable real-time processing of high resolution scanner output, the coding has been parallelized and implemented on a transputer system. For comparison, the test image was coded using existing (lossless) methods giving compression rates of 2-7. The best of these, a combination of predictive and binary arithmetic coding was modified and optimized achieving a compression rate of 9.
Analysis of bit-stuffing codes and lower bounds on capacity for 2-D constrained arrays using quasistationary measures

A method for designing quasistationary probability measures for two-dimensional (2-D) constraints is presented. This measure is derived from a modified bit-stuff coding scheme and it gives the capacity of the coding scheme. This provides a constructive lower bound on the capacity of the 2-D constraint. The main examples are checkerboard codes with binary elements. The capacity for one instance of the modified bit-stuffing for the 2-D runlength-limited RLL(2,/spl infin/) constraint is calculated to be 0.4414 bits/symbol. For the constraint given by a minimum (1-norm) distance of 3 between 1s a code with capacity 0.3497 bits/symbol is given.
On-board processing of video image sequences

The ldquoatmosphere-space interactions monitorrdquo (ASIM) is a payload to be mounted on one of the external platforms of the Columbus module of the International Space Station (ISS). The instruments include six video cameras, six photometers and one X-ray detector. The main scientific objective of the mission is to study transient luminous events (TLE) above severe thunderstorms: the sprites, jets and elves. Other atmospheric phenomena are also studied including aurora, gravity waves and meteors. As part of the ASIM Phase B study, on-board processing of data from the cameras is being developed and evaluated. On-board there are six video cameras each capturing images of 1024times1024 pixels of 12 bpp at a frame rate of 15 fps, thus totalling 1080 Mbits/s. In comparison the average downlink data rate for these images is projected to be 50 kbit/s. This calls for efficient on-board processing to select and compress the data. Algorithms for on-board processing of the image data are presented as well as evaluation of the performance. The main processing steps are event detection, image cropping and image compression. The on-board processing requirements are also evaluated.
Hardware implementation of MPEG analysis and deblocking for video enhancement

In this work, we develop an architecture to implement a deblocking filter to improve the quality of video decoded from MPEG. The filter is controlled by the quantization scale parameter, which is derived from the decoded stream based on a novel algorithm. The hardware implementation is targeting an FPGA device similar to those currently used in post-processing units of high end flat panel TV sets. The designed filter shows good performance in terms of robust signal-to-noise ratio and its implementation meets the area and frequency constraints.
A Multi-Frame Post-Processing Approach to Improved Decoding of H.264/AVC Video

Video compression techniques may yield visually annoying artifacts for limited bitrate coding. In order to improve video quality, a multi-frame based motion compensated filtering algorithm is reported based on combining multiple pictures to form a single super-resolution picture and decimation to the desired format. The algorithm is applied to H.264/AVC decoded sequences and the processing involves a quality estimation based on picture type and local quantization value. Compared with directly decoding, the peak signal to noise ratio (PSNR) of the sequence obtained by the proposed algorithm is improved, and annoying ringing artifacts are effectively suppressed.
Subjective quality of videos displayed with local backlight dimming at different peak white and ambient light levels

In this paper the influence of ambient light and peak white (maximum brightness) of a display on the subjective quality of videos shown with local backlight dimming is examined. A subjective experiment investigating those factors is set-up using high contrast test sequences. The results are firstly analyzed with an ANalysis Of VAriance, which shows significant effect of the Sequence and Algorithms interactions and the Peak White and Ambient Light interactions. This latter allows us to define test cases for which the peak white and ambient light are adapted to one another. An objective model of the subjective grades is then computed using Partial Least Squares regression that achieves 0.68 correlation.
Investigating subjective attributes of quality for videos displayed with local backlight dimming

This paper investigates what composes the quality of videos displayed on LCD with local backlight dimming. In a subjective experiment, participants assessed the level of nine attributes defined using the Qualitative Descriptive Analysis method. Results show that three attributes (Contrast, Change over time and Grain) vary significantly depending on the backlight dimming algorithm. Predicting global quality grades from the attributes using Partial Least Square (PLS) regression does not provide satisfying results. However, the attributes can be represented through objective measures and a similar model mixing attributes and one objective measure can predict global quality satisfyingly.
Low complexity video encoding for UAV inspection

In this work we present several methods for fast integer motion estimation of videos recorded aboard an Unmanned Aerial Vehicle (UAV). Different from related work, the field depth is not considered to be consistent. The novel methods designed for low complexity MV prediction in H.264/AVC and analysis hereof include histogram-based prediction, constant global motion, and modification of the candidate sets in the Enhanced Predictive Zonal Search (EPZS). The results verify the applicability of the methods with a speed-up factor of integer motion estimation up to 2–4. Initial results for UAV infrared (IR) video are also provided.
Modeling the Quality of Videos Displayed With Local Dimming Backlight at Different Peak White and Ambient Light Levels

This paper investigates the impact of ambient light and peak white (maximum brightness of a display) on the perceived quality of videos displayed using local backlight dimming. Two subjective tests providing quality evaluations are presented and analyzed. The analyses of variance show significant interactions of the factors peak white and ambient light with the perceived quality. Therefore, we proceed to predict the subjective quality grades with objective measures. The rendering of the frames on liquid crystal displays with light emitting diodes backlight at various ambient light and peak white levels is computed using a model of the display. Widely used objective quality metrics are applied based on the rendering models of the videos to predict the subjective evaluations. As these predictions are not satisfying, three machine learning methods are applied: partial least square regression, elastic net, and support vector regression. The elastic net method obtains the best prediction accuracy with a spearman rank order correlation coefficient of 0.71, and two features are identified as having a major influence on the visual quality.
A configurable FPGA FEC unit for Tb/s optical communication

Decoding of FEC (forward error correction) for optical communication beyond 1 Tb/s is investigated. A configurable single FPGA solution is presented having configurations supporting bit-rates in the range from 40 Gb/s to 1.6 Tb/s. The design allows for trade-offs of bit-rate, footprint, and latency within the resources of the FPGA. A proof-of-concept lab experiment at 40 Gb/s was conducted and pre-FEC — post-FEC performance validated with simulated results.
Multi-hypothesis transform domain Wyner-Ziv video coding including optical flow

Transform Domain Wyner-Ziv (TDWZ) video coding is an efficient Distributed Video coding solution providing new features such as low complexity encoding, by mainly exploiting the source statistics at the decoder based on the availability of decoder side information. The accuracy of the decoder side information has a major impact on the performance of TDWZ. In this paper, a novel multi-hypothesis based TDWZ video coding is presented to exploit the redundancy between multiple side information and the source information. The decoder used optical flow for side information calculation. Compared with the best available single estimation mode TDWZ, the proposed multi-hypothesis based TDWZ achieves robustly better Rate-Distortion (RD) performance and the overall improvement is up to 0.6 dB at high bitrate and up to 2 dB compared with the DISCOVER TDWZ video codec.
Wavelet-based image enhancement using fourth order PDE

The presence of noise interference signal may cause problems in signal and image analysis; hence signal and image de-noising is often used as a preprocessing stage in many signal processing applications. In this paper, a new method is presented for image de-noising based on fourth order partial differential equations (PDEs) and wavelet transform. In the existing wavelet thresholding methods, the final noise reduced image has limited improvement. It is due to keeping the approximate coefficients of the image unchanged. These coefficients have the main information of the image. Since noise affects both the approximate and detail coefficients, in this research, the anisotropic diffusion technique for noise reduction is applied on the approximation band to alleviate the deficiency of the existing wavelet thresholding methods. The proposed method was applied on several standard noisy images and the results indicate superiority of the proposed method over the existing wavelet-based image de-noising, anisotropic diffusion, and wiener filtering techniques.
Objective assessment of the impact of frame rate on video quality

In this paper, we present a novel objective quality metric that takes the impact of frame rate into account. The proposed metric uses PSNR, frame rate and a content dependent parameter that can easily be obtained from spatial and temporal activity indices. The results have been validated on data from a subjective quality study, where the test subjects have been choosing the preferred path from the lowest quality to the best quality, at each step making a choice in favor of higher frame rate or lower distortion. A comparison with other relevant objective metrics shows that the proposed metric on average provides a more precise correlation with the subjective results.
Block Pickard Models for Two-Dimensional Constraints

In Pickard random fields (PRF), the probabilities of finite configurations and the entropy of the field can be calculated explicitly, but only very simple structures can be incorporated into such a field. Given two Markov chains describing a boundary, an algorithm is presented which determines whether a PRF consistent with the distribution on the boundary and a 2-D constraint exists. Iterative scaling is used as part of the algorithm, which also determines the conditional probabilities yielding the maximum entropy for the given boundary description if a solution exists. A PRF is defined for the domino tiling constraint represented by a quaternary alphabet. PRF models are also presented for higher order constraints, including the no isolated bits (n.i.b.) constraint, and a minimum distance 3 constraint by defining super symbols on blocks of binary symbols.
Artifact reduction of compressed images and video combining adaptive fuzzy filtering and directional anisotropic diffusion

Fuzzy filtering is one of the recently developed methods for reducing distortion in compressed images and video. In this paper, we combine the powerful anisotropic diffusion equations with fuzzy filtering in order to reduce the impact of artifacts. Based on the directional nature of the blocking and ringing artifacts, we have applied directional anisotropic diffusion. Besides that, the selection of the adaptive threshold parameter for the diffusion coefficient has also improved the performance of the algorithm. Experimental results on JPEG compressed images as well as MJPEG and H.264 compressed videos show improvement in artifact reduction of the proposed algorithm over other directional and spatial fuzzy filters.
Bi-level image compression with tree coding

Presently, tree coders are the best bi-level image coders. The current ISO standard, JBIG, is a good example. By organising code length calculations properly a vast number of possible models (trees) can be investigated within reasonable time prior to generating code. Three general-purpose coders are constructed by this principle. A multi-pass free tree coding scheme produces superior compression results for all test images. A multi-pass fast free template coding scheme produces much better results than JBIG for difficult images, such as halftonings. Rissanen's algorithm 'Context' is presented in a new version that without sacrificing speed brings it close to the multi-pass coders in compression performance.
An upper bound on the entropy of constrained 2D fields

An upper bound on the entropy of constrained 2D fields is presented. The constraints have to be symmetric in (at least) one of the two directions. The bound generalizes (in a weaker form) the bound of Calkin and Wilf ) which is valid only for processes with symmetric transfer matrices. Results are given for constraints specified by run-length limits and minimum distance between pixels of the same color.
Lossless image data sequence compression using optimal context quantization

Context based entropy coding often faces the conflict of a desire for large templates and the problem of context dilution. We consider the problem of finding the quantizer Q that quantizes the K-dimensional causal context C/sub i/=(X(i-t/sub 1/), X(i-t/sub 2/), ..., X(i-t/sub K/)) of a source symbol X/sub i/ into one of M conditioning states. A solution giving the minimum adaptive code length for a given data set is presented (when the cost of the context quantizer is neglected). The resulting context quantizers can be used for sequential coding of the sequence X/sub 0/, X/sub 1/, X/sub 2/, .... A coding scheme based on binary decomposition and context quantization for coding the binary decisions is presented and applied to digital maps and /spl alpha/-plane sequences. The optimal context quantization is also used to evaluate existing heuristic context quantizations.
Temporal Probabilistic Shaping for Mitigation of Nonlinearities in Optical Fiber Systems

In this paper, finite state machine sources (FSMSs) are used to shape quadrature amplitude modulation (QAM) for nonlinear transmission in optical fiber communication systems. The previous optimization algorithm for FSMSs is extended to cover an average power constraint, thus enabling temporal optimization with multiamplitude constellations output, such as QAM. The optimized source results in increased received SNR and, thereby, increased achievable information rates (AIR)s under memoryless assumption. The AIR is increased even further when taking the channel and transmitter memory into account via trellis processing at the receiver. Significant gains are reported in the highly nonlinear region of transmission for an FSMS of up to second order and 16QAM and particularly for unrepeated transmission. At the optimal launch power of WDM transmission, the FSMS order needs to be increased further in order to notably outperform previous probabilistic shaping schemes.
Low-complexity JPEG-based progressive video codec for wireless video transmission

This paper discusses the question of video codec enhancement for wireless video transmission of high definition video data taking into account constraints on memory and complexity. Starting from parameter adjustment for JPEG2000 compression algorithm used for wireless transmission and achieving the best possible results by tuning settings, this work proceeds to develop a low-complexity progressive codec based on JPEG, which is compared to the tuned JPEG2000. Comparison to H.264/SVC for this codec is also given. As the results show, our simple solution on low rates can compete with JPEG2000 and H.264/SVC for specific video content.
Rate-distortion-complexity optimization of fast motion estimation in H.264/MPEG-4 AVC

This paper presents an operational method for optimizing integer motion estimation in real-time H.264 encoding with respect to the trade-off between rate-distortion and complexity. This three-parameter problem is converted into a more tractable two-parameter problem by a simple approximative elimination of either the rate or the distortion term by converting small differences in the term to be eliminated. This paper also presents an H.264-enhanced implementation of the fast EPZS motion estimation algorithm, which adds three early-stop criteria controlled by predefined thresholds allowing it to stop after 16 16 and 8 8 block types and for each additional reference frame. Results for interlaced SDTV material are presented with indications of the applicability of the operational method when applied to the presented motion estimation procedure. For example, a speed-up by a factor of 4 compared to a basic H.264-adapted EPZS implementation is achieved at only 1% increase in rate.
Improved side information generation for Distributed Video Coding

As a new coding paradigm, distributed video coding (DVC) deals with lossy source coding using side information to exploit the statistics at the decoder to reduce computational demands at the encoder. The performance of DVC highly depends on the quality of side information. With a better side information generation method, fewer bits will be requested from the encoder and more reliable decoded frames will be obtained. In this paper, a side information generation method is introduced to further improve the rate-distortion (RD) performance of transform domain distributed video coding. This algorithm consists of a variable block size based Y, U and V component motion estimation and an adaptive weighted overlapped block motion compensation (OBMC). The proposal is tested and compared with the results of an executable DVC codec released by DISCOVER group (DIStributed COding for Video sERvices). RD improvements on the set of test sequences are observed.
Distributed multi-hypothesis coding of depth maps using texture motion information and optical flow

Distributed Video Coding (DVC) is a video coding paradigm allowing a shift of complexity from the encoder to the decoder. Depth maps are images enabling the calculation of the distance of an object from the camera, which can be used in multiview coding in order to generate virtual views, but also in single view coding for motion detection or image segmentation. In this work, we address the problem of depth map video DVC encoding in a single-view scenario. We exploit the motion of the corresponding texture video which is highly correlated with the depth maps. In order to extract the motion information, a block-based and an optical flow-based methods are employed. Finally we fuse the proposed Side Informations using a multi-hypothesis DVC decoder, which allows us to exploit the strengths of all the proposed methods at the same time.
Factorization properties of the optimal signaling distribution of multi-dimensional QAM constellations

In this work we study the properties of the optimal Probability Mass Function (PMF) of a discrete input to a general Multiple Input Multiple Output (MIMO) channel. We prove that when the input constellation is constructed as a Cartesian product of 1-dimensional constellations, the optimal PMF factorizes into the product of the marginal 1D PMFs. This confirms the conjecture made in , which allows for optimizing the input PMF efficiently when the rank of the MIMO channel grows. The proof is built upon the iterative Blahut-Arimoto algorithm. We show that if the initial PMF is factorized, the PMF on each successive step is also factorized. Since the algorithm converges to the optimal PMF, it must therefore also be factorized.
No-Reference Video Quality Assessment Using Codec Analysis

A no-reference (NR) video quality assessment (VQA) method is presented for videos distorted by H.264/Advanced Video Coding (AVC) and MPEG-2. The assessment is performed without access to the bitstream. Instead, we analyze and estimate coefficients based on decoded pixels. The approach involves distinguishing between the two types of videos, estimating the level of quantization used in the I-frames, and exploiting this information to assess the video quality. To do this for H.264/AVC, the distribution of the discrete cosine transform-coefficients after intra-prediction and deblocking are modeled. To obtain VQA features for H.264/AVC, we propose a novel estimation method of the quantization in H.264/AVC videos without bitstream access, which can also be used for peak signal-to-noise ratio estimation. The results from the MPEG-2 and H.264/AVC analysis are mapped to a perceptual measure of video quality by support vector regression. For validation purposes, the proposed method was tested on two databases. In both cases, a good performance compared with state of the art full, reduced, and NR VQA algorithms was achieved.
Nonlinear Phase Noise Compensation in Experimental WDM Systems With 256QAM

Nonlinear phase noise (NLPN) is studied in an experimental wavelength division multiplexed (WDM) system operating at 256QAM. Extremely narrow linewidth lasers (<inline-formula><tex-math notation="LaTeX">$<$</tex-math> </inline-formula>1 kHz) at the transmitter and the receiver allow for extracting the phase part of the nonlinear noise in a Raman amplified link. Based on the experimental data, the autocorrelation function of the NLPN is estimated and it matches the theoretical predictions. Several algorithms are examined as candidates for tracking and compensating the NLPN. It is shown that algorithms that exploit the distribution of the NLPN achieve higher gains than standard methods, which only exploit the correlation properties. Up to 300 km, reach increase is achieved for a 5 <inline-formula><tex-math notation="LaTeX">$\times$</tex-math></inline-formula> 10 GBaud WDM system with base distance of up to 1600 km. The gains are comparable to the gains of single-channel digital backpropagation, with even further improvements from the combination of both techniques.
Quality assessment of adaptive bitrate videos using image metrics and machine learning

Adaptive bitrate (ABR) streaming is widely used for distribution of videos over the internet. In this work, we investigate how well we can predict the quality of such videos using well-known image metrics, information about the bitrate levels, and a relatively simple machine learning method. Quality assessment of ABR videos is a hard problem, but our initial results are promising. We obtain a Spearman rank order correlation of 0.88 using content-independent cross-validation.
Temporal scalability comparison of the H.264/SVC and distributed video codec

The problem of the multimedia scalable video streaming is a current topic of interest. There exist many methods for scalable video coding. This paper is focused on the scalable extension of H.264/AVC (H.264/SVC) and distributed video coding (DVC). The paper presents an efficiency comparison of SVC and DVC having reduced encoder complexity. Moreover, temporal scalability is described for these two algorithms, and it is analyzed and compared.