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2019 Data Compression Conference (DCC)最新文献

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Improving Cube-to-ERP Conversion Performance with Geometry Features of 360 Video Structure 利用360视频结构的几何特征提高立方体到erp的转换性能
2019 Data Compression Conference (DCC) Pub Date : 2019-03-26 DOI: 10.1109/DCC.2019.00103
Chunyu Lin, Ning Yu, H. Bai, Meiqin Liu, Yao Zhao
{"title":"Improving Cube-to-ERP Conversion Performance with Geometry Features of 360 Video Structure","authors":"Chunyu Lin, Ning Yu, H. Bai, Meiqin Liu, Yao Zhao","doi":"10.1109/DCC.2019.00103","DOIUrl":"https://doi.org/10.1109/DCC.2019.00103","url":null,"abstract":"360 videos provide an omnidirectional view of the scene with extremely large data. Therefore, representing 360 videos with less data has become more and more important. Cube format is such a popular representation of 360 videos. However, we have to convert cube to Equirectangula(ERP) for displaying convenience. In this paper, we enhance Cube-to-ERP conversion performance by joint using Convolutional Neural Network(CNN) and classical interpolation method. The optimal threshold of boundary is derived according to geometry features of the cube-to-ERP format. This threshold is the guidance of how to combine CNN and classical interpolation method. Our experiment results prove that the derived threshold has a certain degree of guiding significance. Furthermore, we propose a new evaluation criterion with the help of Marsaglia model. It is much easier and more accurate to evaluate geometry conversion process.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115401006","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: 1
Lossy Source Coding via Deep Learning 通过深度学习的有损源代码编码
2019 Data Compression Conference (DCC) Pub Date : 2019-03-26 DOI: 10.1109/DCC.2019.00009
Qing Li, Yang Chen
{"title":"Lossy Source Coding via Deep Learning","authors":"Qing Li, Yang Chen","doi":"10.1109/DCC.2019.00009","DOIUrl":"https://doi.org/10.1109/DCC.2019.00009","url":null,"abstract":"Motivated by a recent work of learning rate distortion approaching posterior via Restricted Boltzmann Machines, we generalize the result to Deep Belief Networks and propose a deep learning based lossy compression for stationary ergodic sources. The compression algorithm consists of two stages, a training stage, which is to learn the posterior with the training data of the same class as the source, and a compression/reproduction stage, which consists of a lossless compression and a lossless reproduction. The theoretical result shows that our algorithm asymptotically achieves the optimum rate-distortion function for stationary ergodic sources, and the experimental results outperform the reported best results.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122785399","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: 5
Enhanced Intra Block Copy with Planar Perspective Transformation for Urban Building Scenes 基于平面透视变换的城市建筑场景增强块内复制
2019 Data Compression Conference (DCC) Pub Date : 2019-03-26 DOI: 10.1109/DCC.2019.00125
Chen Zhang, Qijun Wang, Jiafei Xu, C. Yang
{"title":"Enhanced Intra Block Copy with Planar Perspective Transformation for Urban Building Scenes","authors":"Chen Zhang, Qijun Wang, Jiafei Xu, C. Yang","doi":"10.1109/DCC.2019.00125","DOIUrl":"https://doi.org/10.1109/DCC.2019.00125","url":null,"abstract":"In this paper, we propose an enhanced intra block copy method for intra prediction in HEVC through planar perspective transformation for urban building scenes. Since the imaging plane of the camera is not always fronto-parallel to the facades of buildings (object plane) in the image, repetitive patterns on object plane in 3D space appear with scale shift in the image, and the corresponding redundancy cannot be removed through conventional intra block copy based on translational motion model. To solve this problem, we start with theoretic analysis to perspective transformation, and get that the two-parametered planar perspective transformation is the cause of scale shift. Therefore, intra block copy can be enhanced via rectification through planar perspective transformation, whose detailed parameters are derived through vanishing points detected in the image. To achieve the best performance, rate-distortion optimization is utilized to determine whether planar perspective transformation would be used in intra block copy for coding unit (CU) or not. In this way, we enable much more flexible prediction for both non-local translational and non-local perspective repeated image content. Experimental results show that our proposed method can achieve as the highest as 9.9% and averagely 2.9% bit-rate saving on the test images for urban building scenes compared to conventional intra block copy on HEVC platform.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128700155","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
Separable KLT for Intra Coding in Versatile Video Coding (VVC) 可分离KLT在多用途视频编码(VVC)中的应用
2019 Data Compression Conference (DCC) Pub Date : 2019-03-26 DOI: 10.1109/DCC.2019.00083
Kui Fan, Ronggang Wang, Weisi Lin, Jong-Uk Hou, Ling-Yu Duan, Ge Li, Wen Gao
{"title":"Separable KLT for Intra Coding in Versatile Video Coding (VVC)","authors":"Kui Fan, Ronggang Wang, Weisi Lin, Jong-Uk Hou, Ling-Yu Duan, Ge Li, Wen Gao","doi":"10.1109/DCC.2019.00083","DOIUrl":"https://doi.org/10.1109/DCC.2019.00083","url":null,"abstract":"After the works on the state-of-the-art High Efficiency Video Coding (HEVC) standard, the standard organizations continued to study the potential video coding technologies for the next generation of video coding standard, named Versatile Video Coding (VVC). Transform is a key technique for compression efficiency, and core experiment 6 (CE6) is carried out to explore the transform related coding tools. In this paper, we propose a novel separable transform based on Karhunen-Loève Transform (KLT) to eliminate the horizontal and vertical correlations in the residual samples of intra coding. In the proposed method, the weaknesses of the traditional KLT are addressed. The separable KLT is developed as an alternative transform type in addition to DCT-II, and the transform matrices from 4×4 to 64×64 are trained from intra residual samples. Experimental results show the proposed method can achieve 2.7% bitrate saving averagely on top of the reference software of VVC (VTM-1.1), and the consistent performance improvement on test set also validates the strong generalization capacity of the proposed separable KLT.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122478256","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: 1
Lossy Image Compression with Filter Bank Based Convolutional Networks 基于滤波器组卷积网络的有损图像压缩
2019 Data Compression Conference (DCC) Pub Date : 2019-03-26 DOI: 10.1109/DCC.2019.00010
Shaohui Li, Ziyang Zheng, Wenrui Dai, H. Xiong
{"title":"Lossy Image Compression with Filter Bank Based Convolutional Networks","authors":"Shaohui Li, Ziyang Zheng, Wenrui Dai, H. Xiong","doi":"10.1109/DCC.2019.00010","DOIUrl":"https://doi.org/10.1109/DCC.2019.00010","url":null,"abstract":"Filter bank based convolutional networks (FBCNs) enable efficient separable multiscale and multidirectional decomposition with a convolutional cascade of 1-D radial and directional filter banks. In this paper, we propose a two-stage subband coding framework for FBCN analysis coefficients using a SPIHT-like algorithm and subsequent primitive-based adaptive arithmetic coding (AAC). The SPIHT-like algorithm extends spatial orientation tree to exploit inter-subband dependency between subbands of different scales and directions. Mutual information is estimated for information-theoretical measurement to formulate such dependencies. Various primitives are designed adaptively encode the generated bitstream by fitting its varying lists and passes. Neural networks are leveraged to improve probability estimation for AAC, where nonlinear prediction is made based on contexts regarding scales, directions, locations and significance of analysis coefficients. Experimental results show that the proposed framework improves the lossy coding performance for FBCN analysis coefficients in comparison to the state-of-the-arts subband coding schemes SPIHT.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121368110","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: 5
New Video Codec for High-Quality Video Service and Emerging Applications 用于高质量视频服务和新兴应用的新视频编解码器
2019 Data Compression Conference (DCC) Pub Date : 2019-03-26 DOI: 10.1109/DCC.2019.00039
Kiho Choi, Jianle Chen, Anish Tamse, Haitao Yang, M. Park, S. Ikonin, W. Choi, S. Esenlik
{"title":"New Video Codec for High-Quality Video Service and Emerging Applications","authors":"Kiho Choi, Jianle Chen, Anish Tamse, Haitao Yang, M. Park, S. Ikonin, W. Choi, S. Esenlik","doi":"10.1109/DCC.2019.00039","DOIUrl":"https://doi.org/10.1109/DCC.2019.00039","url":null,"abstract":"This paper proposes a novel video compression scheme for high-quality video service and emerging applications such as 360-degree omnidirectional and high dynamic range video coding. The coding framework supports hierarchical splitting of blocks with binary and ternary-split trees and flexible coding order representations. Moreover, minimal tool set to obtain high precision prediction and compression enhancement has been proposed. Compared to HEVC, bit-rate reduction of around 40% based on objective measures has been shown. This was one of the responses to the Call for Proposals (CfP) for VVC standardization.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127191581","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
Deep Learning Based Angular Intra-Prediction for Lossless HEVC Video Coding 基于深度学习的角内预测无损HEVC视频编码
2019 Data Compression Conference (DCC) Pub Date : 2019-03-26 DOI: 10.1109/DCC.2019.00091
H. Huang, I. Schiopu, A. Munteanu
{"title":"Deep Learning Based Angular Intra-Prediction for Lossless HEVC Video Coding","authors":"H. Huang, I. Schiopu, A. Munteanu","doi":"10.1109/DCC.2019.00091","DOIUrl":"https://doi.org/10.1109/DCC.2019.00091","url":null,"abstract":"n/a","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128951334","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: 11
Bank Select Method for Reducing Symbol Search Operations on Stream-Based Lossless Data Compression 基于流的无损数据压缩中减少符号搜索操作的银行选择方法
2019 Data Compression Conference (DCC) Pub Date : 2019-03-26 DOI: 10.1109/DCC.2019.00123
S. Yamagiwa, Ryuta Morita, Koichi Marumo
{"title":"Bank Select Method for Reducing Symbol Search Operations on Stream-Based Lossless Data Compression","authors":"S. Yamagiwa, Ryuta Morita, Koichi Marumo","doi":"10.1109/DCC.2019.00123","DOIUrl":"https://doi.org/10.1109/DCC.2019.00123","url":null,"abstract":"Dictionary-based lossless data compression algorithms mainly replace a frequent data pattern in the inputted data to a compressed symbol, and to decompress vice versa. The mechanism potentially has an overhead problem regarding the number of symbol matchings in the table. This work focuses on a technique to reduce the number of searches in the dictionary using a bank separation technique. This poster presentation shows design and implementation of the technique applied to LCT-DLT.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"28 4 Suppl 14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131837288","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: 5
Better Than Optimal Huffman Coding? 比最优霍夫曼编码更好?
2019 Data Compression Conference (DCC) Pub Date : 2019-03-26 DOI: 10.1109/DCC.2019.00094
S. T. Klein, Shoham Saadia, Dana Shapira
{"title":"Better Than Optimal Huffman Coding?","authors":"S. T. Klein, Shoham Saadia, Dana Shapira","doi":"10.1109/DCC.2019.00094","DOIUrl":"https://doi.org/10.1109/DCC.2019.00094","url":null,"abstract":"Huffman coding is known to be optimal, yet its dynamic version may yield smaller compressed files. The best known bound is that the number of bits used by dynamic Huffman coding in order to encode a message of n characters is at most larger by n bits than the number of bits required by static Huffman coding. In particular, dynamic Huffman coding can also generate a larger encoded file than the static variant, though in practice the file might often, but not always, be smaller. We propose here a new dynamic Huffman encoding approach, that provably always performs at least as good as static Huffman coding, and may be better than the standard dynamic Huffman coding for certain files.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123913980","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: 2
A New Distributed Source Coding Problem Related to the Classical-Quantum Slepian–Wolf Problem 与经典量子睡狼问题相关的一种新的分布式源编码问题
2019 Data Compression Conference (DCC) Pub Date : 2019-03-26 DOI: 10.1109/DCC.2019.00085
Hachiro Fujita
{"title":"A New Distributed Source Coding Problem Related to the Classical-Quantum Slepian–Wolf Problem","authors":"Hachiro Fujita","doi":"10.1109/DCC.2019.00085","DOIUrl":"https://doi.org/10.1109/DCC.2019.00085","url":null,"abstract":"Suppose there are two correlated sources, one producing classical data and the other producing mixed states with commuting density operators. We combine the two sources into one and call it a classical-quantum source. In this paper, we consider the problem of distributed compression of the classical-quantum source. This is a special case of the classical-quantum Slepian-Wolf problem addressed by Devetak and Winter [1]. Suppose Alice (resp. Bob) receives classical (resp. quantum) data from the classical-quantum source. Alice and Bob, who cannot communicate with each other, want to send their received data to Charlie at the minimum communication cost. We consider two scenarios, the blind and visible scenarios, for Bob's quantum data compression. We formulate our problem in terms of classical information theory and then using some results in classical information theory, we show partial results on the achievable rate region for asymptotically lossless distributed compression of the classical-quantum source in the blind and visible scenarios.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131920459","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
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