Pub Date : 2018-06-01DOI: 10.1109/PCS.2018.8456268
H. Meuel, H. Ackermann, B. Rosenhahn, J. Ostermann
This paper aims at simplified high dynamic range (HDR) image generation with non-modified, conventional camera sensors. One typical HDR approach is exposure bracketing, e.g. with varying shutter speeds. It requires to capture the same scene multiple times at different exposure times. These pictures are then merged into a single HDR picture which typically is converted back to an 8-bit image by using tone-mapping. Existing works on HDR imaging focus on image merging and tone mapping whereas we aim at simplified image acquisition. The proposed algorithm can be used in consumer-level cameras without hardware modifications at sensor level. Based on intermediate samplings of each sensor element during the total (pre-defined) exposure time, we extrapolate the luminance of sensor elements which are saturated after the total exposure time. Compared to existing HDR approaches which typically require three different images with carefully determined exposure times, we only take one image at the longest exposure time. The shortened total time between start and end of image acquisition can reduce ghosting artifacts. The experimental evaluation demonstrates the effectiveness of the algorithm.
{"title":"Physical High Dynamic Range Imaging with Conventional Sensors","authors":"H. Meuel, H. Ackermann, B. Rosenhahn, J. Ostermann","doi":"10.1109/PCS.2018.8456268","DOIUrl":"https://doi.org/10.1109/PCS.2018.8456268","url":null,"abstract":"This paper aims at simplified high dynamic range (HDR) image generation with non-modified, conventional camera sensors. One typical HDR approach is exposure bracketing, e.g. with varying shutter speeds. It requires to capture the same scene multiple times at different exposure times. These pictures are then merged into a single HDR picture which typically is converted back to an 8-bit image by using tone-mapping. Existing works on HDR imaging focus on image merging and tone mapping whereas we aim at simplified image acquisition. The proposed algorithm can be used in consumer-level cameras without hardware modifications at sensor level. Based on intermediate samplings of each sensor element during the total (pre-defined) exposure time, we extrapolate the luminance of sensor elements which are saturated after the total exposure time. Compared to existing HDR approaches which typically require three different images with carefully determined exposure times, we only take one image at the longest exposure time. The shortened total time between start and end of image acquisition can reduce ghosting artifacts. The experimental evaluation demonstrates the effectiveness of the algorithm.","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131689016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/PCS.2018.8456257
Wei Gao, I. Amer, Yang Liu, Gabor Sines
A typical video encoder includes into the generated bit stream Instantaneous Decoder Refresh (IDR) units. This allows random access playback at the receiver side as well as graceful recovery from potential channel errors. Such forced IDR units typically come in repetitive patterns, which may negatively impact the perceived subjective quality if not handled properly. The reason is that the restricted encoding process of an IDR unit results in a different (regardless higher or lower) quality of reconstructed signal compared to the surrounding non-IDR ones. This causes eye-capturing irritating periodical artifacts when it occurs in patterns. This phenomenon gets to be even more pronounced when the intra refresh feature is enabled, since it forces IDR and nonIDR units to co-exist within the same picture, making the quality difference more noticeable. This paper proposes a method to hide such undesired patterns that naturally accompany the intra refresh feature. Two ideas are presented; the first one imposes restrictions that prevent unwanted fluctuations in the quantization levels between different regions of the picture, while the second hides the repetitive pattern by randomly forcing IDR blocks within specific regions of the refreshed picture. Results show that the proposed method results in improvements in subjective quality.
{"title":"A Method to Improve Perceptual Quality of Intra- Refresh-Enabled Low-Latency Video Coding","authors":"Wei Gao, I. Amer, Yang Liu, Gabor Sines","doi":"10.1109/PCS.2018.8456257","DOIUrl":"https://doi.org/10.1109/PCS.2018.8456257","url":null,"abstract":"A typical video encoder includes into the generated bit stream Instantaneous Decoder Refresh (IDR) units. This allows random access playback at the receiver side as well as graceful recovery from potential channel errors. Such forced IDR units typically come in repetitive patterns, which may negatively impact the perceived subjective quality if not handled properly. The reason is that the restricted encoding process of an IDR unit results in a different (regardless higher or lower) quality of reconstructed signal compared to the surrounding non-IDR ones. This causes eye-capturing irritating periodical artifacts when it occurs in patterns. This phenomenon gets to be even more pronounced when the intra refresh feature is enabled, since it forces IDR and nonIDR units to co-exist within the same picture, making the quality difference more noticeable. This paper proposes a method to hide such undesired patterns that naturally accompany the intra refresh feature. Two ideas are presented; the first one imposes restrictions that prevent unwanted fluctuations in the quantization levels between different regions of the picture, while the second hides the repetitive pattern by randomly forcing IDR blocks within specific regions of the refreshed picture. Results show that the proposed method results in improvements in subjective quality.","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131329185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/PCS.2018.8456291
Thorsten Laude, Y. G. Adhisantoso, Jan Voges, Marco Munderloh, J. Ostermann
The current state-of-the-art for standardized video codecs is High Efficiency Video Coding (HEVC) which was developed jointly by ISO/IEC and ITU-T. Recently, the development of two contenders for the next generation of standardized video codecs began: ISO/IEC and ITU-T advance the development of the Joint Exploration Model (JEM), a possible successor of HEVC, while the Alliance for Open Media pushes forward the video codec AV1. It is asserted by both groups that their codecs achieve superior coding efficiency over the state-of-the-art. In this paper, we discuss the distinguishing features of JEM and AV1 and evaluate their coding efficiency and computational complexity under well-defined and balanced test conditions. Our main findings are that JEM considerably outperforms HM and AV1 in terms of coding efficiency while AV1 cannot transform increased complexity into competitiveness in terms of coding efficiency with neither of the competitors except for the all-intra configuration.
{"title":"A Comparison of JEM and AV1 with HEVC: Coding Tools, Coding Efficiency and Complexity","authors":"Thorsten Laude, Y. G. Adhisantoso, Jan Voges, Marco Munderloh, J. Ostermann","doi":"10.1109/PCS.2018.8456291","DOIUrl":"https://doi.org/10.1109/PCS.2018.8456291","url":null,"abstract":"The current state-of-the-art for standardized video codecs is High Efficiency Video Coding (HEVC) which was developed jointly by ISO/IEC and ITU-T. Recently, the development of two contenders for the next generation of standardized video codecs began: ISO/IEC and ITU-T advance the development of the Joint Exploration Model (JEM), a possible successor of HEVC, while the Alliance for Open Media pushes forward the video codec AV1. It is asserted by both groups that their codecs achieve superior coding efficiency over the state-of-the-art. In this paper, we discuss the distinguishing features of JEM and AV1 and evaluate their coding efficiency and computational complexity under well-defined and balanced test conditions. Our main findings are that JEM considerably outperforms HM and AV1 in terms of coding efficiency while AV1 cannot transform increased complexity into competitiveness in terms of coding efficiency with neither of the competitors except for the all-intra configuration.","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114414497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/PCS.2018.8456310
Volker Bruns, T. Richter, Bilal Ahmed, J. Keinert, S. Fößel
JPEG XS is an upcoming lightweight image compression standard that is especially developed to meet the requirements of compressed video-over-IP use cases. It is designed with not only CPU, FPGA or ASIC platforms in mind, but explicitly also targets GPUs. Though not yet finished, the codec is now sufficiently mature to present a first NVIDIA CUDA-based GPU decoder architecture and preliminary performance results. On a 2014 mid-range GPU with 640 cores a 12 bit UHD 4:2:2 (4:4:4) can be decoded with 54 (42) fps. The algorithm scales very well: on a 2017 high-end GPU with 2560 cores the throughput increases to 190 (150) fps. In contrast, an optimized GPU-accelerated JPEG 2000 decoder takes 2x as long for high compression ratios that yield a PSNR of 40 dB and 3x as long for lower compression ratios with a PSNR of over 50 dB.
{"title":"Decoding JPEG XS on a GPU","authors":"Volker Bruns, T. Richter, Bilal Ahmed, J. Keinert, S. Fößel","doi":"10.1109/PCS.2018.8456310","DOIUrl":"https://doi.org/10.1109/PCS.2018.8456310","url":null,"abstract":"JPEG XS is an upcoming lightweight image compression standard that is especially developed to meet the requirements of compressed video-over-IP use cases. It is designed with not only CPU, FPGA or ASIC platforms in mind, but explicitly also targets GPUs. Though not yet finished, the codec is now sufficiently mature to present a first NVIDIA CUDA-based GPU decoder architecture and preliminary performance results. On a 2014 mid-range GPU with 640 cores a 12 bit UHD 4:2:2 (4:4:4) can be decoded with 54 (42) fps. The algorithm scales very well: on a 2017 high-end GPU with 2560 cores the throughput increases to 190 (150) fps. In contrast, an optimized GPU-accelerated JPEG 2000 decoder takes 2x as long for high compression ratios that yield a PSNR of 40 dB and 3x as long for lower compression ratios with a PSNR of over 50 dB.","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126031557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/PCS.2018.8456299
Xuewei Meng, Chuanmin Jia, Shanshe Wang, Xiaozhen Zheng, Siwei Ma
In order to compensate the shortcomings of existing in-loop filters only based on local correlation in video coding standards, many non-local based loop filters with high coding performance and computational complexity are proposed. In this paper, we propose a fast block matching algorithm, adaptive two-step block matching algorithm, based on our previous work, structure-driven adaptive non-local filter (SANF) which is computationally intensive because of the high complexity of block matching and singular value decomposition (SVD). Our proposed algorithm based on image spatial statistical characteristics utilizes fixed template to select adaptive number of similar blocks according to image content, which can reduce up to 75.2% search candidates compared to exhaustive search in SANF and the adaptive determination strategy can remove blocks with less relation to reference block in similar block group which have little help for compression performance, and the remove of them can reduce the computational complexity of SVD. Our proposed optimization algorithm can save encoding and decoding time significantly with negligible performance loss, which achieves 70.7%, 84.4%, 80.82% and 81.95% decoding time saving with only 0.13%, 0.05%, 0.13% and 0.15% increases of BD-rate for AI, RA, LDB and LDP configurations, respectively compared to original SANF in JEM-7.0.
{"title":"Optimized Non-local In-Loop Filter for Video Coding","authors":"Xuewei Meng, Chuanmin Jia, Shanshe Wang, Xiaozhen Zheng, Siwei Ma","doi":"10.1109/PCS.2018.8456299","DOIUrl":"https://doi.org/10.1109/PCS.2018.8456299","url":null,"abstract":"In order to compensate the shortcomings of existing in-loop filters only based on local correlation in video coding standards, many non-local based loop filters with high coding performance and computational complexity are proposed. In this paper, we propose a fast block matching algorithm, adaptive two-step block matching algorithm, based on our previous work, structure-driven adaptive non-local filter (SANF) which is computationally intensive because of the high complexity of block matching and singular value decomposition (SVD). Our proposed algorithm based on image spatial statistical characteristics utilizes fixed template to select adaptive number of similar blocks according to image content, which can reduce up to 75.2% search candidates compared to exhaustive search in SANF and the adaptive determination strategy can remove blocks with less relation to reference block in similar block group which have little help for compression performance, and the remove of them can reduce the computational complexity of SVD. Our proposed optimization algorithm can save encoding and decoding time significantly with negligible performance loss, which achieves 70.7%, 84.4%, 80.82% and 81.95% decoding time saving with only 0.13%, 0.05%, 0.13% and 0.15% increases of BD-rate for AI, RA, LDB and LDP configurations, respectively compared to original SANF in JEM-7.0.","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"375 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124688457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/PCS.2018.8456261
Alexandre Mercat, F. Arrestier, M. Pelcat, W. Hamidouche, D. Ménard
In the last few years, the Internet of Things (IoT) has become a reality. Forthcoming applications are likely to boost mobile video demand to an unprecedented level. A large number of systems are likely to integrate the latest MPEG video standard High Efficiency Video Coding (HEVC) in the long run and will particularly require energy efficiency. In this context, constraining the computational complexity of embedded HEVC encoders is a challenging task, especially in the case of software encoders. The most energy consuming part of a software intra encoder is the determination of the coding tree partitioning, i.e. the size of pixel blocks. This determination usually requires an iterative process that leads to repeating some encoding tasks. State-of-the-art studies have focused on predicting, from “easily” computed characteristics, an efficient coding tree. They have proposed and evaluated independently many characteristics for one-shot quad-tree prediction. In this paper, we present a fair comparison of these characteristics using a Machine Learning approach and a real-time HEVC encoder. Both computational complexity and information gain are considered, showing that characteristics are far from equivalent in terms of coding tree prediction performance.
在过去的几年里，物联网(IoT)已经成为现实。即将推出的应用程序可能会将移动视频需求提升到前所未有的水平。从长远来看，大量的系统可能会集成最新的MPEG视频标准HEVC (High Efficiency video Coding)，并对能效提出了特别的要求。在这种情况下，限制嵌入式HEVC编码器的计算复杂度是一项具有挑战性的任务，特别是在软件编码器的情况下。软件内编码器最耗能的部分是编码树划分的确定，即像素块的大小。这种确定通常需要一个迭代过程，导致重复一些编码任务。最先进的研究集中在预测，从“容易”计算的特征，一个有效的编码树。他们提出并独立评估了单次四叉树预测的许多特征。在本文中，我们使用机器学习方法和实时HEVC编码器对这些特征进行了公平的比较。考虑了计算复杂度和信息增益，表明在编码树预测性能方面，特征远非相等。
{"title":"Machine Learning Based Choice of Characteristics for the One-Shot Determination of the HEVC Intra Coding Tree","authors":"Alexandre Mercat, F. Arrestier, M. Pelcat, W. Hamidouche, D. Ménard","doi":"10.1109/PCS.2018.8456261","DOIUrl":"https://doi.org/10.1109/PCS.2018.8456261","url":null,"abstract":"In the last few years, the Internet of Things (IoT) has become a reality. Forthcoming applications are likely to boost mobile video demand to an unprecedented level. A large number of systems are likely to integrate the latest MPEG video standard High Efficiency Video Coding (HEVC) in the long run and will particularly require energy efficiency. In this context, constraining the computational complexity of embedded HEVC encoders is a challenging task, especially in the case of software encoders. The most energy consuming part of a software intra encoder is the determination of the coding tree partitioning, i.e. the size of pixel blocks. This determination usually requires an iterative process that leads to repeating some encoding tasks. State-of-the-art studies have focused on predicting, from “easily” computed characteristics, an efficient coding tree. They have proposed and evaluated independently many characteristics for one-shot quad-tree prediction. In this paper, we present a fair comparison of these characteristics using a Machine Learning approach and a real-time HEVC encoder. Both computational complexity and information gain are considered, showing that characteristics are far from equivalent in terms of coding tree prediction performance.","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125436474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/PCS.2018.8456267
H. Golestani, Thibaut Meyer, M. Wien
The main idea of this paper is to extract the 3D scene geometry for the observed scene and use it for synthesizing a more precise prediction using Image-Based Rendering (IBR) for motion compensation in a hybrid coding scheme. The proposed method first extracts camera parameters using Structure from Motion (SfM). Then, a Patch-based Multi-View Stereo (PMVS) technique is employed to generate the scene Point-Cloud (PC) only from already decoded key-frames. Since the PC could be really sparse in poorly reconstructed regions, a depth expansion mechanism is also used. This 3D information helps to properly warp textures from the key-frames to the target frame. This IBR-based prediction is then used as an additional reference for motion compensation. In this way, the encoder can choose between the rendered prediction and the regular reference pictures through a rate- distortion optimization. On average, the simulation results show about 2.16% bitrate reduction compared to the reference HEVC implementation, for tested dynamic and static scene video sequences.
本文的主要思想是提取观察场景的三维场景几何形状，并使用基于图像的渲染(IBR)在混合编码方案中进行运动补偿，从而合成更精确的预测。该方法首先利用SfM (Structure from Motion)提取相机参数。然后，采用基于patch的多视点立体(PMVS)技术，仅从已解码的关键帧生成场景点云(PC)。由于PC在重建较差的区域可能非常稀疏，因此还使用了深度扩展机制。这个3D信息有助于正确地将纹理从关键帧扭曲到目标帧。这种基于ibr的预测然后用作运动补偿的附加参考。这样，编码器可以通过率失真优化在渲染的预测图像和常规参考图像之间进行选择。对于测试的动态和静态场景视频序列，仿真结果显示，与参考HEVC实现相比，平均比特率降低了2.16%。
{"title":"Image-Based Rendering using Point Cloud for 2D Video Compression","authors":"H. Golestani, Thibaut Meyer, M. Wien","doi":"10.1109/PCS.2018.8456267","DOIUrl":"https://doi.org/10.1109/PCS.2018.8456267","url":null,"abstract":"The main idea of this paper is to extract the 3D scene geometry for the observed scene and use it for synthesizing a more precise prediction using Image-Based Rendering (IBR) for motion compensation in a hybrid coding scheme. The proposed method first extracts camera parameters using Structure from Motion (SfM). Then, a Patch-based Multi-View Stereo (PMVS) technique is employed to generate the scene Point-Cloud (PC) only from already decoded key-frames. Since the PC could be really sparse in poorly reconstructed regions, a depth expansion mechanism is also used. This 3D information helps to properly warp textures from the key-frames to the target frame. This IBR-based prediction is then used as an additional reference for motion compensation. In this way, the encoder can choose between the rendered prediction and the regular reference pictures through a rate- distortion optimization. On average, the simulation results show about 2.16% bitrate reduction compared to the reference HEVC implementation, for tested dynamic and static scene video sequences.","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129131531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/PCS.2018.8456253
Gonzalo Luzardo, J. Aelterman, H. Luong, W. Philips, Daniel Ochoa, Sven Rousseaux
High Dynamic Range (HDR) displays can show images with higher color contrast levels and peak luminosities than the common Low Dynamic Range (LDR) displays. However, most existing video content is recorded and/or graded in LDR format. To show this LDR content on HDR displays, a dynamic range expansion by using an Inverse Tone Mapped Operator (iTMO) is required. In addition to requiring human intervention for tuning, most of the iTMOs don’t consider artistic intentions inherent to the HDR domain. Furthermore, the quality of their results decays with peak brightness above 1000 nits. In this paper, we propose a fully-automatic inverse tone mapping operator based on mid-level mapping. This allows expanding LDR images into HDR with peak brightness over 1000 nits, preserving the artistic intentions inherent to the HDR domain. We assessed our results using full-reference objective quality metrics as HDR- VDP-2.2 and DRIM. Experimental results demonstrate that our proposed method outperforms the current state of the art.
{"title":"Fully-Automatic Inverse Tone Mapping Preserving the Content Creator’s Artistic Intentions","authors":"Gonzalo Luzardo, J. Aelterman, H. Luong, W. Philips, Daniel Ochoa, Sven Rousseaux","doi":"10.1109/PCS.2018.8456253","DOIUrl":"https://doi.org/10.1109/PCS.2018.8456253","url":null,"abstract":"High Dynamic Range (HDR) displays can show images with higher color contrast levels and peak luminosities than the common Low Dynamic Range (LDR) displays. However, most existing video content is recorded and/or graded in LDR format. To show this LDR content on HDR displays, a dynamic range expansion by using an Inverse Tone Mapped Operator (iTMO) is required. In addition to requiring human intervention for tuning, most of the iTMOs don’t consider artistic intentions inherent to the HDR domain. Furthermore, the quality of their results decays with peak brightness above 1000 nits. In this paper, we propose a fully-automatic inverse tone mapping operator based on mid-level mapping. This allows expanding LDR images into HDR with peak brightness over 1000 nits, preserving the artistic intentions inherent to the HDR domain. We assessed our results using full-reference objective quality metrics as HDR- VDP-2.2 and DRIM. Experimental results demonstrate that our proposed method outperforms the current state of the art.","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129746687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/PCS.2018.8456255
Philippe Hanhart, Yuwen He, Yan Ye, J. Boyce, Z. Deng, Lidong Xu
360-degree video is emerging as a new way of offering immersive visual experience. The quality evaluation of 360- degree video is more difficult compared to the quality evaluation of conventional video. However, to ensure successful development of 360-degree video coding technologies, it is essential to precisely measure both objective and subjective quality. In this paper, an overview of the 360-degree video quality evaluation framework established by the joint video exploration team (JVET) of ITU-T VCEG and ISO/IEC MPEG is provided. This framework aims at reproducing the different processes in the 360-degree video processing workflow that are related to coding. The results of different experiments conducted using the JVET framework are reported to illustrate the impact on objective and subjective quality with different projection formats and codecs.
{"title":"360-Degree Video Quality Evaluation","authors":"Philippe Hanhart, Yuwen He, Yan Ye, J. Boyce, Z. Deng, Lidong Xu","doi":"10.1109/PCS.2018.8456255","DOIUrl":"https://doi.org/10.1109/PCS.2018.8456255","url":null,"abstract":"360-degree video is emerging as a new way of offering immersive visual experience. The quality evaluation of 360- degree video is more difficult compared to the quality evaluation of conventional video. However, to ensure successful development of 360-degree video coding technologies, it is essential to precisely measure both objective and subjective quality. In this paper, an overview of the 360-degree video quality evaluation framework established by the joint video exploration team (JVET) of ITU-T VCEG and ISO/IEC MPEG is provided. This framework aims at reproducing the different processes in the 360-degree video processing workflow that are related to coding. The results of different experiments conducted using the JVET framework are reported to illustrate the impact on objective and subjective quality with different projection formats and codecs.","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124414602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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