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Advanced 3D Motion Prediction for Video Based Point Cloud Attributes Compression 基于点云属性压缩的视频高级3D运动预测
2019 Data Compression Conference (DCC) Pub Date : 2019-03-01 DOI: 10.1109/DCC.2019.00058
Li Li, Zhu Li, Vladyslav Zakharchenko, Jianle Chen
{"title":"Advanced 3D Motion Prediction for Video Based Point Cloud Attributes Compression","authors":"Li Li, Zhu Li, Vladyslav Zakharchenko, Jianle Chen","doi":"10.1109/DCC.2019.00058","DOIUrl":"https://doi.org/10.1109/DCC.2019.00058","url":null,"abstract":"Point cloud media representation format has provided various opportunities for extended reality applications and had become widely used in volumetric content capturing scenarios. At the same time ambiguous storage format representations and network throughput are key problems for wide adoption of this media format. Compression algorithms in corresponding standard activities are aimed to solve this problem. MPEG-I standard has an aim of creating the point cloud compression methodology relying on existing video coding hardware implementations. In scope of the state-of-the-art video-based dynamic point cloud (DPC) compression method, similar 3D patches may be projected in totally different 2D positions in different frames. In this way, the motion vector predictors especially those in the patch boundary may be very inaccurate which may lead to significant bitrate increase. In this paper, we propose to use the reconstructed geometry information to help predict the motion vector more accurately and improve the coding efficiency of the attribute video. First, we propose to use the motion vector of the co-located blocks in the geometry frame as a merge candidate of the current block in the attribute frame. Second, we perform a motion estimation between the current reconstructed point cloud with only the geometry information and the reference point cloud to find the corresponding block. The motion information derived is used as motion vector predictor of the current block in the attribute frame. As far as we can see, this is the first work using the geometry information to compress the attribute in the DPC compression scenario. Significant compression efficiency is achieved with this new 3D point cloud geometry derived motion prediction scheme when compared with the state-of-the-art DPC compression method.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132410626","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}
引用次数: 0
Wide Angular Intra Prediction for Versatile Video Coding 多用途视频编码的广角内预测
2019 Data Compression Conference (DCC) Pub Date : 2019-03-01 DOI: 10.1109/DCC.2019.00013
Liang Zhao, Xin Zhao, Shan Liu, Xiang Li, J. Lainema, G. Rath, F. Urban, Fabien Racapé
{"title":"Wide Angular Intra Prediction for Versatile Video Coding","authors":"Liang Zhao, Xin Zhao, Shan Liu, Xiang Li, J. Lainema, G. Rath, F. Urban, Fabien Racapé","doi":"10.1109/DCC.2019.00013","DOIUrl":"https://doi.org/10.1109/DCC.2019.00013","url":null,"abstract":"This paper presents a technical overview of Wide Angular Intra Prediction (WAIP) that was adopted into the test model of Versatile Video Coding (VVC) standard. Due to the adoption of flexible block partitioning using binary and ternary splits, a Coding Unit (CU) can have either a square or a rectangular block shape. However, the conventional angular intra prediction directions, ranging from 45 degrees to -135 degrees in clockwise direction, were designed for square CUs. To better optimize the intra prediction for rectangular blocks, WAIP modes were proposed to enable intra prediction directions beyond the range of conventional intra prediction directions. For different aspect ratios of rectangular block shapes, different number of conventional angular intra prediction modes were replaced by WAIP modes. The replaced intra prediction modes are signaled using the original signaling method. Simulation results reportedly show that, with almost no impact on the run-time, on average 0.31% BD-rate reduction is achieved for intra coding using VVC test model (VTM).","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116198266","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}
引用次数: 28
Polynomial Time Algorithms for Constructing Optimal AIFV Codes 构造最优AIFV码的多项式时间算法
2019 Data Compression Conference (DCC) Pub Date : 2019-03-01 DOI: 10.1109/DCC.2019.00031
M. Golin, Elfarouk Harb
{"title":"Polynomial Time Algorithms for Constructing Optimal AIFV Codes","authors":"M. Golin, Elfarouk Harb","doi":"10.1109/DCC.2019.00031","DOIUrl":"https://doi.org/10.1109/DCC.2019.00031","url":null,"abstract":"Huffman Codes are \"optimal\" Fixed-to-Variable (FV) codes if every source symbol can only be encoded by one codeword. Relaxing this constraint permits constructing better FV codes. More specifically, recent work has shown that AIFV codes can beat Huffman coding. AIFV codes construct a set of different coding trees between which the code alternates and are only \"almost instantaneous\" (AI). This means that decoding a word might require a delay of a finite number of bits. Current algorithms for constructing optimal AIFV codes are iterative processes that construct progressively \"better sets\" of code trees. The processes have been proven to finitely converge to the optimal code but with no known bounds on the convergence time. This paper derives a geometric interpretation of the space of AIFV codes. This permits the development of new polynomially time-bounded iterative procedures for constructing optimal AIFV codes. For the simplest case we show that a binary search procedure can replace the current iterative process. For the more complicated cases we describe how to frame the problem as a linear programming problem with an exponential number of constraints but a polynomial time separability oracle. This permits using the Grotschel, Lovasz and Schrijver ellipsoid method to solve the problem in a polynomial number of steps.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131227824","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}
引用次数: 8
Near-Lossless ℓ∞-Constrained Image Decompression via Deep Neural Network 基于深度神经网络的近无损约束图像解压缩
2019 Data Compression Conference (DCC) Pub Date : 2019-03-01 DOI: 10.1109/DCC.2019.00011
Xi Zhang, Xiaolin Wu
{"title":"Near-Lossless ℓ∞-Constrained Image Decompression via Deep Neural Network","authors":"Xi Zhang, Xiaolin Wu","doi":"10.1109/DCC.2019.00011","DOIUrl":"https://doi.org/10.1109/DCC.2019.00011","url":null,"abstract":"Recently a number of CNN-based techniques were proposed to remove image compression artifacts. As in other restoration applications, these techniques all learn a mapping from decompressed patches to the original counterparts under the ubiquitous L2 metric. However, this approach is incapable of restoring distinctive image details which may be statistical outliers but have high semantic importance (e.g., tiny lesions in medical images). To overcome this weakness, we propose to incorporate an ℓ∞ fidelity criterion in the design of neural network so that no small, distinctive structures of the original image can be dropped or distorted. Experimental results demonstrate that the proposed method outperforms the state-of-the-art methods in ℓ∞ error metric and perceptual quality, while being competitive in L2 error metric as well. It can restore subtle image details that are otherwise destroyed or missed by other algorithms. Our research suggests a new machine learning paradigm of ultra high fidelity image compression that is ideally suited for applications in medicine, space, and sciences.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133662030","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}
引用次数: 9
Fast PU Early Termination Algorithm Based on WMSE for ERP Video Intra Prediction 基于WMSE的ERP视频帧内预测快速PU提前终止算法
2019 Data Compression Conference (DCC) Pub Date : 2019-03-01 DOI: 10.1109/DCC.2019.00126
Mengmeng Zhang, Renbo Su, Zhi Liu, Fuqi Mao, Wen Yue
{"title":"Fast PU Early Termination Algorithm Based on WMSE for ERP Video Intra Prediction","authors":"Mengmeng Zhang, Renbo Su, Zhi Liu, Fuqi Mao, Wen Yue","doi":"10.1109/DCC.2019.00126","DOIUrl":"https://doi.org/10.1109/DCC.2019.00126","url":null,"abstract":"As virtual reality becomes more popular, 360-degree video coding becomes challenging. Projected videos of 360-degree videos and traditional videos are both planar videos, but the projected videos have distortion whose degree depends on the latitude. Traditional coding algorithms cannot effectively adapt to this feature, and 360-degree videos typically have high resolution and frame rate, which results in a high coding complexity. In this study, a fast prediction unit (PU) early termination algorithm based on weighted mean square error (WMSE) of 360-degree video is proposed. In the proposed algorithm, WMSE is used as a basis for the early termination of further PU partitioning. First, the full intra prediction process of the current CU is performed. After that, the similarity between the current CU and its four sub-CUs is calculated using WMSE for 2N×2N; and distortion between predicted and original blocks is calculated using WMSE for N×N. the similarity and distortion is used to terminate PU partitioning. The experimental results show that the algorithm achieves a 31% time reduction, and an average of only 0.3% of the luma Bjontegaard delta rate (BD rate) increases.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134000719","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}
引用次数: 3
Intra-Prediction Side-Information Reduction Based on Gradient Boundary 基于梯度边界的预测内侧信息约简
2019 Data Compression Conference (DCC) Pub Date : 2019-03-01 DOI: 10.1109/DCC.2019.00055
Lucas Nissenbaum, Mumin Jin, J. Lim
{"title":"Intra-Prediction Side-Information Reduction Based on Gradient Boundary","authors":"Lucas Nissenbaum, Mumin Jin, J. Lim","doi":"10.1109/DCC.2019.00055","DOIUrl":"https://doi.org/10.1109/DCC.2019.00055","url":null,"abstract":"Recent developments in intra-prediction show the advantage of increasing the number of prediction directions. This trend can be observed in most previous standards, and should remain in the future. However, increasing the number of intra-prediction directions incurs a non-negligible side-information bit-rate. To reduce this side-information bit-rate, we propose a method to adaptively decide whether to use a larger or smaller set of candidate intra-prediction directions by simply evaluating the maximum gradient magnitude, theoretically motivated by the prediction inaccuracy model. In this scenario, we can achieve most of the gain from using the larger intra-prediction direction set while only requiring a small amount of side-information. This method yields a significant BD-rate reduction on multiple resolutions of images using fixed block-size when implemented in a simplified HEVC-based encoder.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131869701","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}
引用次数: 0
Deep Frame Interpolation for Video Compression 视频压缩的深帧插值
2019 Data Compression Conference (DCC) Pub Date : 2019-03-01 DOI: 10.1109/DCC.2019.00068
Jean Bégaint, Franck Galpin, P. Guillotel, C. Guillemot
{"title":"Deep Frame Interpolation for Video Compression","authors":"Jean Bégaint, Franck Galpin, P. Guillotel, C. Guillemot","doi":"10.1109/DCC.2019.00068","DOIUrl":"https://doi.org/10.1109/DCC.2019.00068","url":null,"abstract":"Deep neural networks have been recently proposed to solve video interpolation tasks. Given a past and future frame, such networks can be trained to successfully predict the intermediate frame(s). In the context of video compression, these architectures could be useful as an additional inter-prediction mode. Current inter-prediction methods rely on block-matching techniques to estimate the motion between consecutive frames. This approach has severe limitations for handling complex non-translational motions, and is still limited to block-based motion vectors. This paper presents a deep frame interpolation network for video compression aiming at solving the previous limitations, i.e. able to cope with all types of geometrical deformations by providing a dense motion compensation. Experiments with the classical bi-directional hierarchical video coding structure demonstrate the efficiency of the proposed approach over the traditional tools of the HEVC codec.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115035098","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}
引用次数: 12
Compressive-Sensed Image Coding via Multi-layer Closed-Loop Prediction 基于多层闭环预测的压缩感知图像编码
2019 Data Compression Conference (DCC) Pub Date : 2019-03-01 DOI: 10.1109/DCC.2019.00074
Zan Chen, Xingsong Hou, Ling Shao, Yuan Huang
{"title":"Compressive-Sensed Image Coding via Multi-layer Closed-Loop Prediction","authors":"Zan Chen, Xingsong Hou, Ling Shao, Yuan Huang","doi":"10.1109/DCC.2019.00074","DOIUrl":"https://doi.org/10.1109/DCC.2019.00074","url":null,"abstract":"These years have seen the advance of compressive sensing (CS), but the CS-based image coding scheme still has a poor rate-distortion (R-D) performance compared with the traditional image coding techniques. In this paper, we propose an image coding scheme based on the CS paradigm via multi-layer closed-loop prediction. In the scheme, we divide CS measurements into multi-layers and predict a particular layer's measurements with all its preceding layers' measurements, which can reduce the redundancies between CS measurements efficiently. The produced measurement residuals are then quantized into binary codes, which are tremendously reduced compared to quantizing the CS measurements directly. Furthermore, We provide a non-local low-rank CS reconstruction algorithm corresponding to our multi-layer closed-loop prediction scheme. Experimental results verify that the proposed scheme can significantly outperform JPEG2000, and the reconstruction quality of our scheme is no worse or even better than that of HEVC-Intra.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123070517","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}
引用次数: 0
Speckle Reduction for Efficient Coding of Experimental Holograms 实验全息图高效编码中的斑点减少
2019 Data Compression Conference (DCC) Pub Date : 2019-03-01 DOI: 10.1109/DCC.2019.00069
Marco V. Bernardo, E. Fonseca, A. Pinheiro, P. Fiadeiro, Manuela Pereira
{"title":"Speckle Reduction for Efficient Coding of Experimental Holograms","authors":"Marco V. Bernardo, E. Fonseca, A. Pinheiro, P. Fiadeiro, Manuela Pereira","doi":"10.1109/DCC.2019.00069","DOIUrl":"https://doi.org/10.1109/DCC.2019.00069","url":null,"abstract":"In previous work, a digital hologram compression scheme for representation on the object plane was proposed. Compression on object plane for experimental holograms and Computer-Generated Holograms (CGH) proves to be a very efficient model that outperforms the compression on the hologram plane. However, the compression gain is more relevant in CGHs. The difference between experimental holograms and CGHs is related to the fact that CGHs are less affected by speckle noise that is a characteristic of experimental holograms. In the current work, to improve the coding efficiency of the hologram compression scheme is proposed the reduction of speckle noise of experimental holograms. The compression scheme defines a base layer where a 2D version of the object is coded with an image codec standard. The efficiency of this step is much higher in case of CGH when compared to experimental holograms. However, after performing speckle noise reduction before any compression a similar compression efficiency is found. Since the speckle noise reduction is performed only on amplitude data without affecting the phase, is still possible to render 3D features such as depth map, multi-view or to recover holographic interference patterns for further 3D visualization.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122144087","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}
引用次数: 0
Numerical Pattern Mining Through Compression 通过压缩的数字模式挖掘
2019 Data Compression Conference (DCC) Pub Date : 2019-03-01 DOI: 10.1109/DCC.2019.00019
Tatiana P. Makhalova, S. Kuznetsov, A. Napoli
{"title":"Numerical Pattern Mining Through Compression","authors":"Tatiana P. Makhalova, S. Kuznetsov, A. Napoli","doi":"10.1109/DCC.2019.00019","DOIUrl":"https://doi.org/10.1109/DCC.2019.00019","url":null,"abstract":"Pattern Mining (PM) has a prominent place in Data Science and finds its application in a wide range of domains. To avoid the exponential explosion of patterns different methods have been proposed. They are based on assumptions on interestingness and usually return very different pattern sets. In this paper we propose to use a compression-based objective as a well-justified and robust interestingness measure. We define the description lengths for datasets and use the Minimum Description Length principle (MDL) to find patterns that ensure the best compression. Our experiments show that the application of MDL to numerical data provides a small and characteristic subsets of patterns describing data in a compact way.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"30 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122677117","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}
引用次数: 4
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