发布求助
文献互助 智能选刊 最新文献

2015 Data Compression Conference最新文献

筛选
英文 中文
Palette-Based Coding in the Screen Content Coding Extension of the HEVC Standard HEVC标准的屏幕内容编码扩展中基于调色板的编码
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.79
Xiaoyu Xiu, Yuwen He, R. Joshi, M. Karczewicz, P. Onno, Christophe Gisquet, G. Laroche
{"title":"Palette-Based Coding in the Screen Content Coding Extension of the HEVC Standard","authors":"Xiaoyu Xiu, Yuwen He, R. Joshi, M. Karczewicz, P. Onno, Christophe Gisquet, G. Laroche","doi":"10.1109/DCC.2015.79","DOIUrl":"https://doi.org/10.1109/DCC.2015.79","url":null,"abstract":"This paper provides a technical overview of palette-based coding that was adopted into the test model for the screen content coding (SCC) extension of High Efficiency Video Coding (HEVC) standard at the 18th JCT-VC meeting. Key techniques that enable the palette mode to deliver significant coding gains for screen contents are highlighted, including palette table generation, palette table coding, and the coding methods for palette indices and escape colors. Proposed and adopted techniques up to the first version of the working draft of HEVC SCC extension and test model SCM-2.0 are presented. Experimental results are provided to evaluate the performance of the palette mode in the SCC extension of HEVC.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123694131","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
A Block-Based Background Model for Surveillance Video Coding 基于块的监控视频编码背景模型
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.49
Liming Yin, R. Hu, Shihong Chen, Jing Xiao, Jinhui Hu
{"title":"A Block-Based Background Model for Surveillance Video Coding","authors":"Liming Yin, R. Hu, Shihong Chen, Jing Xiao, Jinhui Hu","doi":"10.1109/DCC.2015.49","DOIUrl":"https://doi.org/10.1109/DCC.2015.49","url":null,"abstract":"Background model can help to improve the compression efficiency for surveillance video coding, but the existing frame-based background model is inefficient in some situations, for example, when a region of background changes frequently or periodically. In this paper, a block-based background model is proposed to solve this problem. We save the background blocks recognized from each reconstructed frame into a buffer, thus the background blocks are collected gradually. At the same time, we compose a new background frame for each frame to be encoded based on the background blocks currently available in the buffer. Compared with the pre-built background frame, the instantly composed background frame often predicts more accurately because of the accumulated information about background. Experimental results show that the proposed model achieves better rate-distortion performance over the existing frame-based model in most cases, while keeping almost the same computation complexity.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121688952","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
R-(lambda) Model Based Improved Rate Control for HEVC with Pre-Encoding 基于R-(lambda)模型的预编码HEVC改进速率控制
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.35
Jiangtao Wen, Meiyuan Fang, Minhao Tang, Kuang Wu
{"title":"R-(lambda) Model Based Improved Rate Control for HEVC with Pre-Encoding","authors":"Jiangtao Wen, Meiyuan Fang, Minhao Tang, Kuang Wu","doi":"10.1109/DCC.2015.35","DOIUrl":"https://doi.org/10.1109/DCC.2015.35","url":null,"abstract":"In this paper, we proposed a new rate control algorithm for High Efficiency Video Coding (HEVC), the latest video coding standard from the ITU/ISO [1]. We use the information of pre-encoded 16×16 coding units (CUs) to estimate the characteristics of the largest coding unit (LCU). Based on the estimates, the proposed R-λ model can be refined before the real encoding process. This is in contrast to rate control algorithms such as that in the HEVC reference software, where the model is updated based on a previously encoded picture. Experimental results show that the proposed rate control scheme can achieve accurate rate control with a BD-PSNR gain up to 5.37dB, compared to the state-of-the-art rate control algorithm in the HEVC test model (HM) 16.0. The largest PSNR improvement was over 6dB.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115705481","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: 25
Lossless Coding Extensions for JPEG JPEG的无损编码扩展
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.11
T. Richter
{"title":"Lossless Coding Extensions for JPEG","authors":"T. Richter","doi":"10.1109/DCC.2015.11","DOIUrl":"https://doi.org/10.1109/DCC.2015.11","url":null,"abstract":"The issue of backwards compatible image and video coding gained some attention in both MPEG and JPEG, let it be as extension for HEVC, let it be as the JPEG XT standardization initiative of the SC29WG1 committee. The coding systems work all on the principle of a base layer operating in the low-dynamic range regime, using a tone-mapped version of the HDR material as input, and an extension layer invisible to legacy applications. The extension layer allows implementations conforming to the full standard to reconstruct the original image in the high-dynamic range regime. What is also common to all approaches is the rate-allocation problem: How can one split the rate between base and extension layer to ensure optimal coding? In this work, an explicit answer is derived for a simplified model of a two-layer compression system in the high bit-rate approximation. For a HDR to LDR tone mapping that approximates the well-known sRGB non-linearity of ? = 2.4 and a Laplacian probability density function, explicit results in the form of the Lambert-W-function are derived. The theoretical results are then verified in experiments using a JPEG XT demo implementation.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"243 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123996824","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
Range Selection Queries in Data Aware Space and Time 数据感知空间和时间中的范围选择查询
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.53
M. O. Külekci, Sharma V. Thankachan
{"title":"Range Selection Queries in Data Aware Space and Time","authors":"M. O. Külekci, Sharma V. Thankachan","doi":"10.1109/DCC.2015.53","DOIUrl":"https://doi.org/10.1109/DCC.2015.53","url":null,"abstract":"On a given vector X = (x<sub>1</sub>, x<sub>2</sub>,..., x<sub>n</sub>) of integers, the range selection (i, j, k) query is finding the k-th smallest integer in (x<sub>i</sub>, x<sub>i+1</sub>,..., x<sub>j</sub>) for any (i, j, k) such that 1 ≤ i ≤ j ≤ n, and 1 ≤ k ≤ j - i + 1. Previous studies on the problem kept X intact and proposed data structures that occupied additional O(n · log n) bits of space over the X itself that answer the queries in logarithmic time. In this study, we replace X and encode all integers in it via a single wavelet tree by using S = n · log u + Σ<sub>∀i</sub> log x<sub>i</sub> + o(n · log u + Σ<sub>∀i</sub> log x<sub>i</sub>) bits, where u is the number of distinct ⌊log x<sub>i</sub>⌋ values observed in X. Notice that u is at most 32 (64) for 32-bit (64-bit) integers and when x<sub>i</sub> > u, the space used for x<sub>i</sub> in the proposed data structure is less then the Elias-δ coding of x<sub>i</sub>. Besides data-aware coding of X, the range selection is performed in O(log u + log x') time where x' is the k-th smallest integer in the queried range. This somewhat adaptive result interestingly achieves the range selection regardless of the size of X, and totally depends on the actual answer of the query. In summary, to the best of our knowledge, we present the first algorithm using data-aware space and time for the general range selection problem.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126053330","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
Coding and Enhancement in Wireless Acoustic Sensor Networks 无线声传感器网络的编码与增强
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.20
Adel Zahedi, Jan Østergaard, S. H. Jensen, P. Naylor, S. Bech
{"title":"Coding and Enhancement in Wireless Acoustic Sensor Networks","authors":"Adel Zahedi, Jan Østergaard, S. H. Jensen, P. Naylor, S. Bech","doi":"10.1109/DCC.2015.20","DOIUrl":"https://doi.org/10.1109/DCC.2015.20","url":null,"abstract":"We formulate a new problem which bridges between source coding and enhancement in wireless acoustic sensor networks. We consider a network of wireless microphones, each of which encoding its own measurement under a covariance matrix distortion constraint and sending it to a fusion center. To process the data at the center, we use a recent spatio-temporal prediction filter. We assume that a weighted sum-rate for the network is specified. The problem is to allocate optimal distortion matrices to the nodes in order to achieve a maximum output SNR at the fusion center after processing the received data, while the weighted sum-rate for the network is no more than the specified value. We formulate this problem as an optimization problem for which we derive a set of equalities imposed on the solution by studying the KKT conditions. In particular, for the special case of scalar sources with two microphones and a sum-rate constraint, we derive the distortion allocation in closed form and will show that if the given sum-rate is higher than a critical value, the stationary points from the KKT conditions lead to distortion allocations which maximize the output SNR of the filter.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128060131","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
Universal Compression of Memoryless Sources over Large Alphabets via Independent Component Analysis 基于独立分量分析的大字母无记忆源的通用压缩
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.48
Amichai Painsky, Saharon Rosset, M. Feder
{"title":"Universal Compression of Memoryless Sources over Large Alphabets via Independent Component Analysis","authors":"Amichai Painsky, Saharon Rosset, M. Feder","doi":"10.1109/DCC.2015.48","DOIUrl":"https://doi.org/10.1109/DCC.2015.48","url":null,"abstract":"Many applications of universal compression involve sources such as text, speech and image, whose alphabet is extremely large. In this work we propose a conceptual framework in which a large alphabet memory less source is decomposed into multiple 'as independent as possible' sources whose alphabet is much smaller. This way we slightly increase the average codeword length as the compressed symbols are no longer perfectly independent, but at the same time significantly reduce the overhead redundancy resulted by the large alphabet of the observed source. Our proposed algorithm, based on a generalization of the Binary Independent Component Analysis, shows to efficiently find the ideal trade-off so that the overall compression size is minimal. We demonstrate our framework on memory less draws from a variety of natural languages and show that the redundancy we achieve is remarkably smaller than most commonly used methods.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"2540 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128739267","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: 6
Kernel Machine Classification Using Universal Embeddings 使用通用嵌入的核机分类
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.61
P. Boufounos, H. Mansour
{"title":"Kernel Machine Classification Using Universal Embeddings","authors":"P. Boufounos, H. Mansour","doi":"10.1109/DCC.2015.61","DOIUrl":"https://doi.org/10.1109/DCC.2015.61","url":null,"abstract":"Summary form only given. Visual inference over a transmission channel is increasingly becoming an important problem in a variety of applications. In such applications, low latency and bit-rate consumption are often critical performance metrics, making data compression necessary. In this paper, we examine feature compression for support vector machine (SVM)-based inference using quantized randomized embeddings. We demonstrate that embedding the features is equivalent to using the SVM kernel trick with a mapping to a lower dimensional space. Furthermore, we show that universal embeddings - a recently proposed quantized embedding design - approximate a radial basis function (RBF) kernel, commonly used for kernel-based inference. Our experimental results demonstrate that quantized embeddings achieve 50% rate reduction, while maintaining the same inference performance. Moreover, universal embeddings achieve a further reduction in bit-rate over conventional quantized embedding methods, validating the theoretical predictions.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122600094","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
Near-Optimal Compression for Compressed Sensing 压缩感知的近最优压缩
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.31
Rayan Saab, Rongrong Wang, Ö. Yilmaz
{"title":"Near-Optimal Compression for Compressed Sensing","authors":"Rayan Saab, Rongrong Wang, Ö. Yilmaz","doi":"10.1109/DCC.2015.31","DOIUrl":"https://doi.org/10.1109/DCC.2015.31","url":null,"abstract":"In this note we study the under-addressed quantization stage implicit in any compressed sensing signal acquisition paradigm. We also study the problem of compressing the bitstream resulting from the quantization. We propose using Sigma-Delta (ΣΔ) quantization followed by a compression stage comprised of a discrete Johnson-Lindenstrauss embedding, and a subsequent reconstruction scheme based on convex optimization. We show that this encoding/decoding method yields near-optimal rate-distortion guarantees for sparse and compressible signals and is robust to noise. Our results hold for sub-Gaussian (including Gaussian and Bernoulli) random compressed sensing measurements, and they hold for high bit-depth quantizers as well as for coarse quantizers including 1-bit quantization.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116639616","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
Adaptive Submodular Dictionary Selection for Sparse Representation Modeling with Application to Image Super-Resolution 稀疏表示建模的自适应子模字典选择及其在图像超分辨率中的应用
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.29
Yangmei Shen, Wenrui Dai, H. Xiong
{"title":"Adaptive Submodular Dictionary Selection for Sparse Representation Modeling with Application to Image Super-Resolution","authors":"Yangmei Shen, Wenrui Dai, H. Xiong","doi":"10.1109/DCC.2015.29","DOIUrl":"https://doi.org/10.1109/DCC.2015.29","url":null,"abstract":"This paper proposes an adaptive dictionary learning approach based on sub modular optimization. A candidate atom set is constructed based on multiple bases from the combination of analytic and trained dictionaries. With the low-frequency components by the analytic DCT atoms, high-resolution dictionaries can be inferred through online learning to make efficient approximation with rapid convergence. It is formulated as a combinatorial optimization for approximate sub modularity, which is suitable for sparse representation based on dictionaries with arbitrary structures. In single-image super-resolution, the proposed scheme has been demonstrated to improve the reconstruction performance in comparison with double sparsity dictionary in terms of both objective and subjective restoration quality.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128073767","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
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信