nils-herrmann/clean_scirepeval huggingface dataset:
Probabilistic Approach for Predicting the Size of Coding Units in the Quad-Tree Structure of the Quality and Spatial Scalable HEVC

The scalable extension of HEVC (known as SHVC), the recent scalable video coding standard, results in an improved compression performance at the cost of significant increase in computational coding complexity. One of the main factors that contribute to the SHVC encoder complexity is choosing the best partitioning structure for the coding tree units (CTUs). Our study focuses on developing a scheme for predicting the CTU structure in the quality and spatial scalable extension of HEVC. The proposed scheme uses the CTU partitioning structure of the already encoded CTUs in the enhancement layers (ELs) and base layer (BL) to predict the coding unit sizes of the to-be-encoded CTUs in the EL. Performance evaluations confirm that our proposed complexity reduction scheme significantly reduces the execution time of the SHVC encoder, while maintaining the overall quality of the coded streams.
Compression of high dynamic range video using the HEVC and H.264/AVC standards

The existing video coding standards such as H.264/AVC and High Efficiency Video Coding (HEVC) have been designed based on the statistical properties of Low Dynamic Range (LDR) videos and are not accustomed to the characteristics of High Dynamic Range (HDR) content. In this study, we investigate the performance of the latest LDR video compression standard, HEVC, as well as the recent widely commercially used video compression standard, H.264/AVC, on HDR content. Subjective evaluations of results on an HDR display show that viewers clearly prefer the videos coded via an HEVC-based encoder to the ones encoded using an H.264/AVC encoder. In particular, HEVC outperforms H.264/AVC by an average of 10.18% in terms of mean opinion score and 25.08% in terms of bit rate savings.
Joint MPEG-2 coding for multi-program broadcasting of pre-recorded video

We developed a cost-effective operational system suitable for digital TV, video on demand, and high definition TV broadcast over satellite networks with limited bandwidth. This MPEG-2 based system is easy to implement and allows the joint video coding of multiple video programs. Compared to present broadcast operations and for the same level of picture quality, our system greatly increases the number of video streams transmitted in each channel. As a result, either a large number of transponders can be freed up to carry real-time broadcasting or the level of the transmitted picture quality can be significantly increased, By switching from tape storage to video server technology, the need for numerous (expensive) playback VTR systems at the headend is eliminated. In addition, the majority of the complete MPEG-2 encoders are replaced by much less complex MPEG-2 transcoders. All this means significant savings for the broadcast stations. In addition to the gain in bandwidth and the reduction in cost, our system speeds up the encoding process by six fold.
Fast block-size partitioning using empirical rate-distortion models for MPEG-2 to H.264/AVC transcoding

We present an efficient H.264/AVC block-size partitioning prediction method, which is based on our proposed empirical rate and distortion models. Compared to other state-of-the-art transcoding methods, and for the same rate-distortion performance, our proposed algorithm requires the least computational complexity, reaching a 73 % reduction in variable block-size motion estimation for SDTV sequences, and 71% reduction for CIF sequences.
Efficient Chrominance Compensation for MPEG2 to H.264 Transcoding

Although open-loop transcoding is known as the most computational efficient transcoding structure, it is also known to introduce many distortions in the transcoded video. This paper addresses the chrominance distortions resulting from the open-loop MPEG2 to H.264 transcoding structure and proposes algorithms to compensate for the chrominance distortions. The open-loop structure is replaced by a closed-loop transcoding structure, which provides high-quality video by removing the chrominance distortions, resulting in an average of 6 dB picture quality improvement.
Efficient Motion Re-Estimation With Rate-Distortion Optimization for MPEG-2 to H.264/AVC Transcoding

One objective in MPEG-2 to H.264/advanced video coding transcoding is to improve the H.264/AVC compression ratio by using more advanced macroblock encoding modes. The motion re-estimation process is by far the most time-consuming process in this type of video transcoding. In this paper, we present an efficient H.264/AVC block size partitioning prediction algorithm for MPEG-2 to H.264/AVC transcoding applications. Our algorithm uses rate-distortion optimization techniques and predicted initial motion vectors to estimate block size partitioning. It is also shown that using block size partitioning smaller than 8 × 8 (i.e., 8 × 4, 4 × 8, and 4 × 4) results in negligible compression improvements, and thus these sizes should be avoided in transcoding. Experimental results show that, compared to the state-of-the-art transcoding scheme, our transcoder yields similar rate-distortion performance, while the computational complexity is significantly reduced, requiring an average of 29% of the computations. Compared to the full-search scheme, our proposed algorithm reduces the computational complexity by about 99.47% for standard-definition television sequences and 98.66% for common intermediate format sequences. Compared to UMHexagonS, the fast motion estimation algorithm used in H.264/AVC, the experimental results show that our proposed algorithm is a better trade-off between computational complexity and picture quality.
An Entropy-based Inverse Tone Mapping Operator for High Dynamic Range Applications

Conversion of existing image and video content to High Dynamic Range (HDR) using inverse Tone Mapping Operator (iTMO) is expected to open new market opportunities for studios and content owners. In this paper, we propose a novel high visual quality iTMO that addresses shortcomings of existing approaches, yielding HDR image quality worth the expectations of the emerging HDR technology. Our method can deal with all types of standard dynamic range (SDR) image content, ranging from dark to bright scenes. Our approach follows the Human Visual System (HVS) characteristic of being more sensitive to luminance changes in dark areas than bright and normal ones, expanding each of these areas accordingly. Our subjective evaluation demonstrates that our proposed operator on average outperforms existing state-of-the-art operators in terms of overall brightness and contrast of the output HDR image.
Visually Favorable Tone-Mapping With High Compression Performance in Bit-Depth Scalable Video Coding

In bit-depth scalable video coding, the tone-mapping scheme used to convert high-bit-depth to eight-bit videos is an essential yet very often ignored component. In this paper, we demonstrate that an appropriate choice of a tone-mapping operator can improve the coding efficiency of bit-depth scalable encoders. We present a new tone-mapping scheme that delivers superior compression efficiency while adhering to a predefined base layer perceptual quality. We develop numerical models that estimate the base layer bit-rate (Rb), the enhancement layer bitrate (Re), and the mismatch (QL) between the resulting low dynamic range (LDR) base-layer signal and the predefined base layer representation. Our proposed tone curve is given by the solution of an optimization problem which minimizes a weighted sum of Rb, Re, and QL. The problem formulation also considers the temporal effect of tone-mapping by adding a constraint to the optimization problem that suppresses flickering artifacts. We also propose a technique with which to tone-map a high-bit-depth video directly in a compression-friendly color space (e.g., one luma and two chroma channels) without converting to the RGB domain. Experimental results show that we can save up to 40% of the total bit-rate (or 3.5 dB PSNR improvement for the same bitrate), and, in general, about 20% bit-rate savings can be achieved.
Logo insertion transcoding for H.264/AVC compressed video

H.264/AVC quickly gains ground in many aspects of video applications, due to its superior coding performance. Inserting a company logo into H.264/AVC compressed video streams has been a highly desirable application in the TV telecasting industry. In this paper, we propose a novel and efficient logo-insertion scheme for H.264/AVC compressed videos. Our proposed scheme overcomes the numerous coding dependencies, and minimizes the changes to the original compressed videos. Experimental results show that our proposed transcoding scheme achieves extraordinary video quality and significantly reduces the bit rate and computational cost. Compared with the cascaded transcoding scheme, our proposed logo-insertion method achieves an average of 1.16 dB PSNR increase, or a 68.6% bit-rate reduction. Our scheme also dramatically reduces the total transcoding time and the motion-estimation time by at least 67.2% and 97.4%, respectively.
Quality of experience for the horizontal pixel parallax adjustment of stereoscopic 3D videos

When capturing stereoscopic 3D video, video distortions can be avoided by setting up the cameras in parallel. Unfortunately, the resulting 3D scene appears to be in front of the screen, which is uncomfortable for the viewers. This problem can be solved by modifying the horizontal pixel parallax, which brings the picture on and behind the screen. We employ an algorithm that extracts and matches features from both left and right video sequences to automatically shift the video frames so that the closest object to the screen has zero pixel parallax. We then perform subjective tests to show that this parallax-adjusting process significantly increases the 3D quality of experience by 19.86%.
A study on the relationship between depth map quality and the overall 3D video quality of experience

The emergence of multiview displays has made the need for synthesizing virtual views more pronounced, since it is not practical to capture all of the possible views when filming multiview content. View synthesis is performed using the available views and depth maps. There is a correlation between the quality of the synthesized views and the quality of depth maps. In this paper we study the effect of depth map quality on perceptual quality of synthesized view through subjective and objective analysis. Our evaluation results show that: 1) 3D video quality depends highly on the depth map quality and 2) the Visual Information Fidelity index computed between the reference and distorted depth maps has Pearson correlation ratio of 0.75 and Spearman rank order correlation coefficient of 0.67 with the subjective 3D video quality.
Modified H.264 intra prediction for compression of video and images captured with a color filter array

Most consumer digital cameras capture color information with a single light sensor and a color filter array (CFA). In these cameras, only one color sample (red, green or blue) is captured at each pixel location. This paper presents a modified H.264 intra prediction scheme for compressing image and video data captured with a color filter array. The H.264 intra prediction modes are modified for the green channel to account for the fact that the green data is not sampled in a rectangular manner in the Bayer pattern, the most popular CFA design. The proposed method increases the compression efficiency of I frames on the green channel by up to 1.2 dB.
Visual color difference evaluation of standard color pixel representations for high dynamic range video compression

With the recent introduction of High Dynamic Range (HDR) and Wide Color Gamut (WCG) technologies, viewers' quality of experience is highly enriched. To distribute HDR videos over a transmission pipeline, color pixels need to be quantized into integer code-words. Linear quantization is not optimal since the Human Visual System (HVS) do not perceive light in a linear fashion. Thus, perceptual transfer functions (PTFs) and color pixel representations are used to convert linear light and color values into a non-linear domain, so that they correspond more closely to the response of the human eye. In this work, we measure the visual color differences caused by different PTFs and color representation with 10-bit quantization. Our study encompasses all the visible colors of the BT.2020 gamut at different representative luminance levels. Visual color differences are predicted using a perceptual color error metric (CIE ΔE2000). Results show that visible color distortion can already occur before any type of video compression is performed on the signal and that choosing the right PTF and color representation can greatly reduce these distortions and effectively enhance the quality of experience.
High Dynamic Range versus Standard Dynamic Range compression efficiency

High Dynamic Range (HDR) image and video technology aims at conveying the full range of perceptible shadow and highlight details with sufficient precision. HDR is regarded by many experts as the next evolution in digital media. However, industrial broadcasters have concerns regarding the bandwidth overhead that this new technology entails. While many consider that broadcasting HDR content would increase bandwidth requirements by around 20%, this number is based on studies where, in addition to the SDR main stream, HDR-related side information is conveyed. A recent subjective evaluation reported that encoding HDR video content in a single layer might require less bandwidth than its associated SDR version. Similar results were discussed in the MPEG ad-hoc group on High Dynamic Range and Wide Color Gamut. In this article, we explain how having more information can result in lower bandwidth requirements. To this end, we describe several limitations of the human vision system that, when exploited, optimize the HDR distribution pipeline for a human observer. Our theoretical assumption about the higher efficiency of HDR is backed up by a statistical analysis of pixel distribution in real images. The Spatial Index objective metric also reconfirms our assumption.
A high-quality fixed-length compression scheme for color images

We present a new compression method which compresses 8/spl times/8 picture blocks by fixed-length codewords. The compression operation is performed on the discrete cosine transforms, DCT, of each block. As a result, our method combines the distinct advantage of being fixed-length with the high image quality obtained by the DCT based compression methods. Our method has excellent error-resistance characteristics since it does not have the synchronization and error propagation problems inherent in variable-length coding methods.
Rate-distortion optimization for high dynamic range video coding

The genuine viewing quality of High Dynamic Range (HDR) data brought an evolution to content production and display manufacture markets. However, the efficiency of compression and transmission of HDR content still needs to be improved. In this paper we modify the H.264/AVC standard to better characterize HDR content. We propose a new Lagrangian multiplier that strikes a balance between the bit-rate and distortion of the HDR video. The updated Lagrange multiplier was implemented on the H.264/AVC reference software. Our experiment results show that the HDR-VDP2 quality scores of the videos encoded by the HDR-accustomed encoder are higher than the ones encoded with the reference encoder. Moreover, subjective tests confirmed that the visual quality of the compressed HDR videos using our proposed method is higher than the one encoded by the reference codec1.
An Efficient Statistical Intra-mode Prediction Method for H.264

H.264 is a new codec that achieves roughly half of the bit-savings over MPEG2 and MPEG4 for a given quality. One of the features of H.264 is that allows intra frames to be predicted from previously encoded macroblocks in the same frame. This prediction is currently based on a simple algorithm that utilizes the encoded modes of the adjacent macroblocks. While this method is fast, it is often inaccurate, especially at high bitrates. In this paper a new adaptive statistical method is proposed that increases prediction accuracy by over 100% in certain situations. This improvement in accuracy results in the reduction of bits required for each intra frame
A Flickering Reduction Scheme for Tone Mapped HDR Video

The current state-of-the-art Tone Mapping Operators (TMOs) yield acceptable results when applied to High Dynamic Range (HDR) images. However, if they are applied on HDR video sequences, they may cause visual artifacts such as visual noise, flickering, ghosting and brightness and color inconsistencies. Among these artifacts, visual noise and flickering are believed to be the most annoying ones for the viewers. In this work, we propose a novel, automated, real-time solution to address the flickering artifact. Our approach uses a statistical based approach to detect scene changes and distinguish them from other visual changes that cause a flickering effect. An adaptive temporal low pass filter is applied on the tone mapping curve to efficiently reduce flickering, while preserving the artistic intention of scene changes.
Random forests-based 2D-to-3D video conversion

An efficient 2D-to-3D video conversion method using Random Forests (RF) machine learning algorithm is proposed. Our approach incorporates multiple monocular cues based on the characteristics of the 3D human visual depth perception (such as texture variation, motion parallax, haze, perspective, occlusion, sharpness and vertical coordination of image pixels) in order to model the depth map of the recorded scene. Performance evaluations show that our RF-based approach outperforms a state-of-the-art motion parallax-based technique by providing more realistic depth information for the scene. Moreover the subjective comparison of results (obtained by viewers watching the generated stereo video sequences on a 3D display system) confirms the higher 3D picture quality obtained by our RF-based method.
Performance evaluation of single layer HDR video transmission pipelines

Thanks to the recent developments in both High Dynamic Range (HDR) content creation and HDR consumer displays, HDR technology is now mature enough for consumer TV broadcasting. Considering that HDR displays have been introduced to the consumer market just recently, backward compatible broadcasting approaches that can also address the Standard Dynamic Range (SDR) displays are preferred during this transition period. While several backward compatible single layer approaches have been proposed for HDR content delivery, there is no comprehensive study on the subjective quality of the delivered content on both SDR and HDR displays. In this work, we investigate the performance of two single layer HDR delivery pipelines, namely HDR10 and SDR10 through three sets of subjective test experiments. The effect of different video preprocessing and post-processing methods used in the HDR10 and SDR10 pipelines on the visual quality of the HDR and SDR outputs is investigated in these comprehensive tests. The analysis of the results shows that the HDR10 pipeline can achieve superior HDR quality compared to that of the SDR10 while the SDR subjective quality of the HDR10 pipeline is comparable to that of the SDR10 pipeline. Therefore, it is concluded that HDR10 can be used as a backward compatible single layer pipeline addressing both HDR and SDR displays. It is also shown in this work that by addressing the display in 4:4:4 mode, the SDR subjective quality of the HDR10 pipeline is further improved compared to the 4:2:0 mode. The findings of this work can be used as guidelines for addressing both HDR and SDR displays with HDR10 pipeline.
Symmetry-Based Scalable Lossless Compression of 3D Medical Image Data

We propose a novel symmetry-based technique for scalable lossless compression of 3D medical image data. The proposed method employs the 2D integer wavelet transform to decorrelate the data and an intraband prediction method to reduce the energy of the sub-bands by exploiting the anatomical symmetries typically present in structural medical images.  Performance evaluations on a wide range of real 3D medical images show an average improvement of 15% in lossless compression ratios when compared to other state-of-the art lossless compression methods that also provide resolution and quality scalability including 3D-JPEG2000, JPEG2000, and H.264/AVC intra-coding.
Adaptive 3D-HEVC video streaming over congested networks through layer prioritization

Transmission of high quality video over wireless networks is increasingly important as users consume more video on mobile devices. Improvement in display technologies will drive demand for higher quality experiences such as multiview video, at the expense of greater bandwidth requirements. The viewing experience can be disrupted while streaming video due to packet loss caused by network congestion and interference. Packet loss in a 3D-HEVC encoded stream can lead to long periods of rebuffering, causing discomfort. To counter this, we have designed a rate adaptation method that uses the packet buffer size as an indicator of network load. During congestion, it proactively drops packets belonging to layers with less impact. The data from the dropped layers is approximated through view synthesis at the user's device using an error concealment strategy to maintain a higher visual Quality of Experience (QoE). The transmission method is evaluated through simulation using the Vienna LTE-A simulator. The QoE is measured using the received video's PSNR and the frequency/duration of rebuffering. The experimental results demonstrate the performance gains for this approach over the benchmark method.
A fixed-length compression method using the Karhunen-Loeve transform

A compression method is presented which combines the distinct advantage of being fixed length with the visual picture quality of transform-based coding methods. This method compresses the Karhunen-Loeve transform coefficients of 8/spl times/8 pixel blocks of the picture and attains a compression ratio of 15.37:1 for color images. Compared to the absolute moment block truncation coding, the other known fixed length compression method, our method improves the compression ratio by 68% and significantly improves the visual quality of the reconstructed picture.
A new signal model and identification algorithm for hidden semi-Markov signals

Markovian models form a powerful tool for modelling physical signals. In this approach, a signal generation model is employed, and its parameters are estimated from signal samples. We present a novel signal generation model for hidden semi-Markov models, HSMMs. Our model results in a significantly easier and more efficient parameter identification method. Instead of the constant probabilities presently used for modelling state transitions, we use state transition probabilities that are state-duration dependant. We then develop a parameter identification algorithm based on the maximum likelihood criterion. Our numerical results show that our parameter identification algorithm can successfully, and more efficiently, estimate the actual values of the model parameters of an HSMM signal.