Pub Date : 2018-06-24DOI: 10.1109/PCS.2018.8456282
Karina Jaskolka, André Kaup
Many visual quality metrics are used to measure the quality of lossy compressed images and videos, and are integrated in the rate-distortion optimization of hybrid video codecs. However, most of the metrics focus on the average objective quality in a picture. In certain applications, like medical image processing, the maximum absolute error should be more weighted. In this paper, the rate-distortion optimization of HEVC is extended by integrating this error metric. Thus, rate, average error, and maximum absolute error are jointly optimized. Furthermore, a weighting factor α is included into the calculation of the optimization for balancing the ratio between average and maximum absolute error. For HEVC intra with $alpha =0.25$ an average maximum absolute error reduction of −25.63 can be achieved, while the bitrate increases slightly by 0.59%. Furthermore, the visual quality of the medical volumes improves and the data fidelity increases, i.e. less block artifacts appear and less structure disappear.
{"title":"Joint Optimization of Rate, Distortion, and Maximum Absolute Error for Compression of Medical Volumes Using HEVC Intra","authors":"Karina Jaskolka, André Kaup","doi":"10.1109/PCS.2018.8456282","DOIUrl":"https://doi.org/10.1109/PCS.2018.8456282","url":null,"abstract":"Many visual quality metrics are used to measure the quality of lossy compressed images and videos, and are integrated in the rate-distortion optimization of hybrid video codecs. However, most of the metrics focus on the average objective quality in a picture. In certain applications, like medical image processing, the maximum absolute error should be more weighted. In this paper, the rate-distortion optimization of HEVC is extended by integrating this error metric. Thus, rate, average error, and maximum absolute error are jointly optimized. Furthermore, a weighting factor α is included into the calculation of the optimization for balancing the ratio between average and maximum absolute error. For HEVC intra with $alpha =0.25$ an average maximum absolute error reduction of −25.63 can be achieved, while the bitrate increases slightly by 0.59%. Furthermore, the visual quality of the medical volumes improves and the data fidelity increases, i.e. less block artifacts appear and less structure disappear.","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130713454","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 : 2018-06-24DOI: 10.1109/PCS.2018.8456289
Tung Nguyen, D. Marpe
This paper presents and discusses an objective performance evaluation of two lines of development for the next generation of video coding schemes: AV1 of the Alliance for Open Media (AOM) and JEM of the Joint Video Exploration Team (JVET). Their already established predecessors, as given by VP9 for AV1 and High Efficiency Video Coding (HEVC) for JEM, serve as references for this evaluation process. A large testset of 28 video sequences with different content, various resolution, and different frame rate has been used as the common data basis. For each sequence and each test candidate, four different rate points associated with varying qualities of reconstruction have been generated. When evaluated in this way relative to their corresponding predecessors, AV1 and JEM show a quite significant coding-efficiency improvement in terms of averaged Bjøntegaard-Delta (BD) bit rate of about 23% and about 32%, respectively. Moreover, this performance study also reveals that there exist different trade-offs between compression efficiency and computational complexity in terms of encoder run time. While the JEM encoder requires a factor of about 8.5 in run time relative to HM, the corresponding run time factor for the AV1 encoder is about 55.8 relative to VP9. When comparing the next-generation coding schemes among each other, this study reveals that AV1 requires an average BD bit-rate overhead of about 49% at the same objective quality while consuming 2.47 times the run time of the JEM encoder.
{"title":"Future Video Coding Technologies: A Performance Evaluation of AV1, JEM, VP9, and HM","authors":"Tung Nguyen, D. Marpe","doi":"10.1109/PCS.2018.8456289","DOIUrl":"https://doi.org/10.1109/PCS.2018.8456289","url":null,"abstract":"This paper presents and discusses an objective performance evaluation of two lines of development for the next generation of video coding schemes: AV1 of the Alliance for Open Media (AOM) and JEM of the Joint Video Exploration Team (JVET). Their already established predecessors, as given by VP9 for AV1 and High Efficiency Video Coding (HEVC) for JEM, serve as references for this evaluation process. A large testset of 28 video sequences with different content, various resolution, and different frame rate has been used as the common data basis. For each sequence and each test candidate, four different rate points associated with varying qualities of reconstruction have been generated. When evaluated in this way relative to their corresponding predecessors, AV1 and JEM show a quite significant coding-efficiency improvement in terms of averaged Bjøntegaard-Delta (BD) bit rate of about 23% and about 32%, respectively. Moreover, this performance study also reveals that there exist different trade-offs between compression efficiency and computational complexity in terms of encoder run time. While the JEM encoder requires a factor of about 8.5 in run time relative to HM, the corresponding run time factor for the AV1 encoder is about 55.8 relative to VP9. When comparing the next-generation coding schemes among each other, this study reveals that AV1 requires an average BD bit-rate overhead of about 49% at the same objective quality while consuming 2.47 times the run time of the JEM encoder.","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"220 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115527640","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.2018.8456258
Jean Bégaint, Franck Galpin, P. Guillotel, C. Guillemot
Video codecs are primarily designed assuming that rigid, block-based, two-dimensional displacements are suitable models to describe the motion taking place in a scene. However, translational models are not sufficient to handle real world motion types such as camera zoom, shake, pan, shearing or changes in aspect ratio. We present here a region-based interprediction scheme to compensate such motion. The proposed mode is able to estimate multiple homography models in order to predict complex scene motion. We also introduce an affine photometric correction to each geometric model. Experiments on targeted sequences with complex motion demonstrate the efficiency of the proposed approach compared to the state-of-the-art HEVC video codec.
{"title":"Region-based models for motion compensation in video compression","authors":"Jean Bégaint, Franck Galpin, P. Guillotel, C. Guillemot","doi":"10.1109/PCS.2018.8456258","DOIUrl":"https://doi.org/10.1109/PCS.2018.8456258","url":null,"abstract":"Video codecs are primarily designed assuming that rigid, block-based, two-dimensional displacements are suitable models to describe the motion taking place in a scene. However, translational models are not sufficient to handle real world motion types such as camera zoom, shake, pan, shearing or changes in aspect ratio. We present here a region-based interprediction scheme to compensate such motion. The proposed mode is able to estimate multiple homography models in order to predict complex scene motion. We also introduce an affine photometric correction to each geometric model. Experiments on targeted sequences with complex motion demonstrate the efficiency of the proposed approach compared to the state-of-the-art HEVC video codec.","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"57 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":"115087782","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.2018.8456271
Olena Chubach, Patrick Garus, M. Wien, J. Ohm
In this paper, a new approach for an improved video coding scheme is presented, which combines hybrid video coding and texture synthesis based on motion distribution statistics. Considering that the utilized texture synthesis approach provides high-quality visual results, while it is developed only for synthe- sizing the identified dynamic textures within a certain area, a new framework is presented, which allows to identify of areas for synthesis and combine conventional coding with synthesis. Also, a new representation and compression of synthesis parameters is presented, which is required due to the updated coding structure. When combining the proposed approach with conventional en- coder (HEVC reference software, HM 16.6), significantly reduced bit rates of the compressed video sequences with the texture replaced can be obtained. Moreover, because the synthesized textures have similar perceptual characteristics to those of the original textures, the video sequences with the texture replaced are also visually similar to the original sequences. Video results are provided online to allow assessing the visual quality of the tested content.
{"title":"Motion-Distribution based Dynamic Texture Synthesis for Video Coding","authors":"Olena Chubach, Patrick Garus, M. Wien, J. Ohm","doi":"10.1109/PCS.2018.8456271","DOIUrl":"https://doi.org/10.1109/PCS.2018.8456271","url":null,"abstract":"In this paper, a new approach for an improved video coding scheme is presented, which combines hybrid video coding and texture synthesis based on motion distribution statistics. Considering that the utilized texture synthesis approach provides high-quality visual results, while it is developed only for synthe- sizing the identified dynamic textures within a certain area, a new framework is presented, which allows to identify of areas for synthesis and combine conventional coding with synthesis. Also, a new representation and compression of synthesis parameters is presented, which is required due to the updated coding structure. When combining the proposed approach with conventional en- coder (HEVC reference software, HM 16.6), significantly reduced bit rates of the compressed video sequences with the texture replaced can be obtained. Moreover, because the synthesized textures have similar perceptual characteristics to those of the original textures, the video sequences with the texture replaced are also visually similar to the original sequences. Video results are provided online to allow assessing the visual quality of the tested content.","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"23 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":"121858228","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.2018.8456238
Max Bläser, J. Schneider, Johannes Sauer, M. Wien
Rectangular block partitioning as it is used in state of the art video codecs such as HEVC can produce visually displeasing artifacts at low bitrates. This effect is particularly noticeable at moving object boundaries. This contribution presents a comprehensive geometry-based block partitioning framework in a post-HEVC codec for motion compensated prediction, intra-prediction and transform coding as a solution. The method is evaluated on the set of sequences defined by the Joint Call for Proposals on Video Compression with Capabilities beyond HEVC [1]. Our contribution aims at visually improving the quality of object boundaries and provides an objective BD-rate gain of 0.82% on average compared to the reference Joint Video Exploration Team (JVET) test model (JEM 7.0).
矩形块分割，因为它被用于最先进的视频编解码器，如HEVC，可以在低比特率下产生视觉上不愉快的工件。这种效果在移动物体边界时尤其明显。这一贡献提出了一个全面的基于几何的块划分框架，用于后hevc编解码器中的运动补偿预测，内部预测和转换编码作为解决方案。该方法在具有超越HEVC功能的视频压缩联合提案(Joint Call for Proposals on Video Compression)[1]定义的序列集上进行评估。我们的贡献旨在从视觉上提高目标边界的质量，与参考的联合视频勘探小组(JVET)测试模型(JEM 7.0)相比，提供了平均0.82%的客观bd率增益。
{"title":"Geometry-based Partitioning for Predictive Video Coding with Transform Adaptation","authors":"Max Bläser, J. Schneider, Johannes Sauer, M. Wien","doi":"10.1109/PCS.2018.8456238","DOIUrl":"https://doi.org/10.1109/PCS.2018.8456238","url":null,"abstract":"Rectangular block partitioning as it is used in state of the art video codecs such as HEVC can produce visually displeasing artifacts at low bitrates. This effect is particularly noticeable at moving object boundaries. This contribution presents a comprehensive geometry-based block partitioning framework in a post-HEVC codec for motion compensated prediction, intra-prediction and transform coding as a solution. The method is evaluated on the set of sequences defined by the Joint Call for Proposals on Video Compression with Capabilities beyond HEVC [1]. Our contribution aims at visually improving the quality of object boundaries and provides an objective BD-rate gain of 0.82% on average compared to the reference Joint Video Exploration Team (JVET) test model (JEM 7.0).","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"10 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":"121341528","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.2018.8456269
Saverio G. Blasi, André Seixas Dias, M. Mrak, Shenglan Huang, E. Izquierdo
Many applications require video content to be encoded and uploaded under specific complexity constraints. While many speed-ups are available in practical video encoder implementations, it is difficult to predict the impact of such techniques on the actual content being encoded and therefore select the best configuration to meet the given constraints. A method is proposed in this paper to automatically select the encoder configuration in order to meet complexity constraints in terms of encoding and uploading time, using a pre-trained encoder configuration transfer matrix. The algorithm ensures that the content is processed within the specified targets, as presented in the experimental evaluation, where it is shown that the encoder can accurately meet specific constraints under a variety of conditions.
{"title":"Complexity-Constrained Video Encoding and Delivery using Configuration Transfer Matrix","authors":"Saverio G. Blasi, André Seixas Dias, M. Mrak, Shenglan Huang, E. Izquierdo","doi":"10.1109/PCS.2018.8456269","DOIUrl":"https://doi.org/10.1109/PCS.2018.8456269","url":null,"abstract":"Many applications require video content to be encoded and uploaded under specific complexity constraints. While many speed-ups are available in practical video encoder implementations, it is difficult to predict the impact of such techniques on the actual content being encoded and therefore select the best configuration to meet the given constraints. A method is proposed in this paper to automatically select the encoder configuration in order to meet complexity constraints in terms of encoding and uploading time, using a pre-trained encoder configuration transfer matrix. The algorithm ensures that the content is processed within the specified targets, as presented in the experimental evaluation, where it is shown that the encoder can accurately meet specific constraints under a variety of conditions.","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"163 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":"124469815","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.2018.8456245
Ziyu Ye, Rana Hegazy, Wei Zhou, P. Cosman, L. Milstein
Disposable wireless video sensors have many potential applications but are subject to stringent energy constraints. We studied the minimization of end-to-end distortion under an total energy constraint, by means of optimizing FEC code rate, number of source bits, and energy allocation between video encoding and wireless transmission. A two-step approach is employed. First, the FEC rate is optimized by exhaustive search. Then a binary-search-based algorithm is proposed to optimize the energy allocation and number of source bits. Experiments show that the algorithm achieves a PSNR gain up to 1dB over some reasonable baselines. A simpler suboptimal algorithm is also tested and exhibits similar performance.
{"title":"Joint Energy Optimization of Video Encoding and Transmission","authors":"Ziyu Ye, Rana Hegazy, Wei Zhou, P. Cosman, L. Milstein","doi":"10.1109/PCS.2018.8456245","DOIUrl":"https://doi.org/10.1109/PCS.2018.8456245","url":null,"abstract":"Disposable wireless video sensors have many potential applications but are subject to stringent energy constraints. We studied the minimization of end-to-end distortion under an total energy constraint, by means of optimizing FEC code rate, number of source bits, and energy allocation between video encoding and wireless transmission. A two-step approach is employed. First, the FEC rate is optimized by exhaustive search. Then a binary-search-based algorithm is proposed to optimize the energy allocation and number of source bits. Experiments show that the algorithm achieves a PSNR gain up to 1dB over some reasonable baselines. A simpler suboptimal algorithm is also tested and exhibits similar performance.","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"84 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":"132631291","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.2018.8456305
Xin Zhao, V. Seregin, A. Said, Kai Zhang, Hilmi E. Egilmez, M. Karczewicz
In existing video coding standards such as H.264/AVC and HEVC, the intra prediction is typically derived using fixed, symmetric prediction filters along the prediction direction, e.g., in planar mode, top-right and bottom-left samples are predicted using symmetric prediction filters. However, in case ofasymmetric availability of neighboring reference samples, the performance of intra prediction filters designed in HEVC may not be optimal. To further refine the intra prediction and achieve higher accuracy of prediction samples, this paper proposes low-complexity refinements over HEVC intra prediction, which are applied on frequently used planar, DC, horizontal and vertical modes. The proposed method only requires simple addition and bit-shift operations on top of HEVC’s intra prediction implementation. Experimental results show that, an average of 0.7% coding gain is achieved for intra coding with no increase in run-time complexity.
{"title":"Low-Complexity Intra Prediction Refinements for Video Coding","authors":"Xin Zhao, V. Seregin, A. Said, Kai Zhang, Hilmi E. Egilmez, M. Karczewicz","doi":"10.1109/PCS.2018.8456305","DOIUrl":"https://doi.org/10.1109/PCS.2018.8456305","url":null,"abstract":"In existing video coding standards such as H.264/AVC and HEVC, the intra prediction is typically derived using fixed, symmetric prediction filters along the prediction direction, e.g., in planar mode, top-right and bottom-left samples are predicted using symmetric prediction filters. However, in case ofasymmetric availability of neighboring reference samples, the performance of intra prediction filters designed in HEVC may not be optimal. To further refine the intra prediction and achieve higher accuracy of prediction samples, this paper proposes low-complexity refinements over HEVC intra prediction, which are applied on frequently used planar, DC, horizontal and vertical modes. The proposed method only requires simple addition and bit-shift operations on top of HEVC’s intra prediction implementation. Experimental results show that, an average of 0.7% coding gain is achieved for intra coding with no increase in run-time complexity.","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"7 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":"124324014","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.2018.8456244
Christian Herglotz, Matthias Kränzler, André Kaup
This paper shows that the processing energy of the decoder software for the next generation video codec can be accurately estimated using a feature based model. Therefore, a model from the literature is taken and extended to account for a high amount of the newly introduced coding modes. It is shown that using a selected set of 60 features, for a large set of more than 800 coded bit streams, a mean estimation error below 5% can be reached. Using the trained parameters of the model, the energy consumption of the decoder can be analyzed in detail such that, e.g., the coding modes consuming most processing energy can be identified. The model can be used inside the encoder for decoding- energy-rate-distortion optimization to generate decoding energy saving bit streams.
{"title":"Decoding Energy Modeling For The Next Generation Video Codec Based On Jem","authors":"Christian Herglotz, Matthias Kränzler, André Kaup","doi":"10.1109/PCS.2018.8456244","DOIUrl":"https://doi.org/10.1109/PCS.2018.8456244","url":null,"abstract":"This paper shows that the processing energy of the decoder software for the next generation video codec can be accurately estimated using a feature based model. Therefore, a model from the literature is taken and extended to account for a high amount of the newly introduced coding modes. It is shown that using a selected set of 60 features, for a large set of more than 800 coded bit streams, a mean estimation error below 5% can be reached. Using the trained parameters of the model, the energy consumption of the decoder can be analyzed in detail such that, e.g., the coding modes consuming most processing energy can be identified. The model can be used inside the encoder for decoding- energy-rate-distortion optimization to generate decoding energy saving bit streams.","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"19 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":"114728902","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.2018.8456240
Yiqun Liu, J. Ostermann
Transform coding and quantization are part of the cornerstones in the current High Efficiency Video Coding (HEVC) standard. They are applied on the residuals from inter-frame or intra predictions. With specified transform matrices, HEVC enhances the coding efficiency vastly compared to Advanced Video Coding (AVC). However, there is still room for improvement. It is observed that the coding of transform coefficients occupies the majority of the bit rate in the stream, since transform matrices in HEVC can not offer the best energy compaction for prediction errors, especially for diagonal features. We introduce scene-based Karhunen-Loeve transform (KLT) in place of the conventional transform for the intra-predicted data for 8 × 8 and 16 × 16 Transform Units (TU). The transform matrices are adaptively designed and later applied according to the prediction modes, quantization steps as well as sizes. The simulation shows great prospect of reducing the bit rate further with KLT, as we gain 3.23%, 7.18% and 6.25% in terms of BD-Rate against HM-16.15 on average for class B, class C and BVI textures respectively, with All-Intra configuration.
{"title":"Scene-based KLT for Intra Coding in HEVC","authors":"Yiqun Liu, J. Ostermann","doi":"10.1109/PCS.2018.8456240","DOIUrl":"https://doi.org/10.1109/PCS.2018.8456240","url":null,"abstract":"Transform coding and quantization are part of the cornerstones in the current High Efficiency Video Coding (HEVC) standard. They are applied on the residuals from inter-frame or intra predictions. With specified transform matrices, HEVC enhances the coding efficiency vastly compared to Advanced Video Coding (AVC). However, there is still room for improvement. It is observed that the coding of transform coefficients occupies the majority of the bit rate in the stream, since transform matrices in HEVC can not offer the best energy compaction for prediction errors, especially for diagonal features. We introduce scene-based Karhunen-Loeve transform (KLT) in place of the conventional transform for the intra-predicted data for 8 × 8 and 16 × 16 Transform Units (TU). The transform matrices are adaptively designed and later applied according to the prediction modes, quantization steps as well as sizes. The simulation shows great prospect of reducing the bit rate further with KLT, as we gain 3.23%, 7.18% and 6.25% in terms of BD-Rate against HM-16.15 on average for class B, class C and BVI textures respectively, with All-Intra configuration.","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"17 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":"121816043","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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