2019 Data Compression Conference (DCC)最新文献

Graph-Based Transform with Weighted Self-Loops for Predictive Transform Coding Based on Template Matching 基于模板匹配的基于图的加权自环变换预测编码

2019 Data Compression Conference (DCC) Pub Date : 2019-05-13 DOI: 10.1109/DCC.2019.00041

Debaleena Roy, T. Guha, Victor Sanchez

引用次数: 1

Clustering Regression Wavelet Analysis for Lossless Compression of Hyperspectral Imagery 高光谱图像无损压缩的聚类回归小波分析

2019 Data Compression Conference (DCC) Pub Date : 2019-05-10 DOI: 10.1109/DCC.2019.00063

Eze Ahanonu, M. Marcellin, A. Bilgin

引用次数: 3

Bi-Intra Prediction for Versatile Video Coding 多用途视频编码的双帧内预测

2019 Data Compression Conference (DCC) Pub Date : 2019-03-26 DOI: 10.1109/DCC.2019.00099

Congrui Li, Zhenghui Zhao, Junru Li, Xianguo Zhang, Siwei Ma, Chen Li

引用次数: 3

RDO-Based Light Field Image Coding Using Convolutional Neural Networks and Linear Approximation 基于卷积神经网络和线性逼近的rdo光场图像编码

2019 Data Compression Conference (DCC) Pub Date : 2019-03-26 DOI: 10.1109/DCC.2019.00066

N. Bakir, W. Hamidouche, O. Déforges, Khouloud Samrouth, Sid Ahmed Fezza, Mohamad Khalil

{"title":"RDO-Based Light Field Image Coding Using Convolutional Neural Networks and Linear Approximation","authors":"N. Bakir, W. Hamidouche, O. Déforges, Khouloud Samrouth, Sid Ahmed Fezza, Mohamad Khalil","doi":"10.1109/DCC.2019.00066","DOIUrl":"https://doi.org/10.1109/DCC.2019.00066","url":null,"abstract":"The increasing penetration of acquisition and display devices for Light Field (LF) content in the consumer market leads to the high proliferation of this new immersive media. This growing interest to LF images thus urgently raises the question of their compression. In this paper, we propose a convolutional neural networks (CNN)-based LF image coding scheme including both Rate Distortion Optimization (RDO) and post-processing steps. First, at the encoder side, the views are rearranged in sparse and dropped set of views. The former are compressed with a standard encoder and transmitted, while the dropped views are either linearly approximated or synthesized by a CNN using the encoded views as input. This choice is made on the basis of the proposed RDO process. At the decoder side, once the dropped views are either linearly approximated or synthesized by a CNN block, a post-processing step is performed to further enhance the quality of the reconstructed views. This post-processing block is based on superpixel to pixel-matching. Experimental results show that the proposed scheme provides views with high visual quality and overcomes the state-of-the-art LF image compression solutions by -30% in terms of BD-BR and 0.62 dB in BD-PSNR.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"54 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":"121008841","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

Generalized Word Equations: A New Approach to Data Compresion 广义词方程:一种新的数据压缩方法

2019 Data Compression Conference (DCC) Pub Date : 2019-03-26 DOI: 10.1109/DCC.2019.00097

Michal Kutwin, Wojciech Plandowski, Artur Zaroda

{"title":"Generalized Word Equations: A New Approach to Data Compresion","authors":"Michal Kutwin, Wojciech Plandowski, Artur Zaroda","doi":"10.1109/DCC.2019.00097","DOIUrl":"https://doi.org/10.1109/DCC.2019.00097","url":null,"abstract":"Let Σ be an alphabet. A generalized word equation, GWE for short, is a set of triples and pairs. A triple is in form (p, q, l) where p, q, l are positive integers. A pair is in form (a, i) where a ∊ S and i is a positive integer. A solution of a word equation e is any word w such that, for each triple (p, q, l) in e, w[p..p + l − 1] = w[q..q + l − 1] and, for each pair (a, i) in e, w[i] = a. If there is only one shortest solution w of e, then we say that e defines w. Observe here that if e defines w, then the solution set of e is {ws : s ∊ Σ*}. The triples and pairs of an equation e are called constraints. If an equation e defines a word w, we say that e is a compressed representation of w. Let G be a GWE with m triples and pairs defining a word w. There is an algorithm reconstructing w from G in O(m+ |w|) worst case time [1]. Therefore decompression is optimal. It is not difficult to prove that in simple modifications of GWE generalize LZ77, LZ78 and LZW algorithms. We consider a natural variant of GWE called pGWE and prove that, for a word w, it is a little more efficent and more general than LZ77 for a reversed word wR. Moreover, it can be proved that GWE approach generalizes the bidirectional scheme. We compared GWE with Straight Line Programs (SLP for short) [2, 3] and prove that if SLP for a word w is of length n, then there is a GWE defining w with n constraints. We are not aware of any reasonable simulation in the other direction. We propose a variant of GWE which compresses an input word w in O(|w|L2) worse case time where L is the longest repeating factor in w. This version was tested on files in Canterbury Corpus. It gives better results than gzip on text files and slightly worse on the other files. It is worth mentioning here that gzip is a result of 20 years studies on LZ77 so it is unfair to compare it with our approach. Our current best approach is significantly worse than bzip2 which is based on the Burrows-Wheeler transform.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"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":"126118976","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

Intra Picture Prediction for Video Coding with Neural Networks 基于神经网络的视频编码图像内预测

2019 Data Compression Conference (DCC) Pub Date : 2019-03-26 DOI: 10.1109/DCC.2019.00053

Philipp Helle, Jonathan Pfaff, Michael Schäfer, R. Rischke, H. Schwarz, D. Marpe, T. Wiegand

引用次数: 27

Signal Reconstruction Performance Under Quantized Noisy Compressed Sensing 量化噪声压缩感知下的信号重构性能

2019 Data Compression Conference (DCC) Pub Date : 2019-03-26 DOI: 10.1109/DCC.2019.00098

Markus Leinonen, M. Codreanu, M. Juntti

引用次数: 1

Recursive Partitioning Search Space Pruning Using Split Cost Prediction 基于分割代价预测的递归分区搜索空间剪枝

2019 Data Compression Conference (DCC) Pub Date : 2019-03-26 DOI: 10.1109/DCC.2019.00034

A. Wieckowski, Jackie Ma, H. Schwarz, D. Marpe, T. Wiegand

引用次数: 5

Decoder-Side Intra Mode Derivation Based on a Histogram of Gradients in Versatile Video Coding 基于梯度直方图的通用视频编码解码器侧模内推导

2019 Data Compression Conference (DCC) Pub Date : 2019-03-26 DOI: 10.1109/DCC.2019.00109

Anthony Nasrallah, E. Mora, T. Guionnet, M. Raulet

{"title":"Decoder-Side Intra Mode Derivation Based on a Histogram of Gradients in Versatile Video Coding","authors":"Anthony Nasrallah, E. Mora, T. Guionnet, M. Raulet","doi":"10.1109/DCC.2019.00109","DOIUrl":"https://doi.org/10.1109/DCC.2019.00109","url":null,"abstract":"Following the finalization of the state-of-the-art video compression standard High Efficiency Video Coding (HEVC) in 2013, there is a growing need for more compression efficiency to handle various new video services and formats. In order to address this need, the ITU-T and MPEG standardization bodies are working together in a Joint Video Expert Team (JVET) group on the standardization of a new video codec called Versatile Video Coding (VVC), aiming to achieve 50% bitrate reduction over HEVC by 2020. One of the solutions that can be proposed in the intra mode is increasing the number of prediction modes, thus allowing more efficient predictions and less energetic residues. However, this solution causes an increase in the signaling cost of the chosen mode, which counterbalances some of the gains obtained by the newly added prediction modes. To address this problem, we propose to derive prediction modes at the decoder, to avoid sending them in the bitstream. This is done by deriving the best prediction mode at the encoder through a gradient calculation performed on each pixel of a well-determined causal region of the image. This method is identically applied at the decoder, thus avoiding the intra mode signaling in the bitstream. This process defines a new coding mode named Decoder side Intra Mode Derivation (DIMD), which competes with other coding modes normally tested at the encoder, including the classical intra coding mode. The proposed method reduces, on average 0.3%, the bitrate used to encode a sequence configured in All Intra (AI), with limited additional decoding complexity (2%).","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"45 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":"126422687","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

Light Field Image Compression with Random Access 随机存取的光场图像压缩

2019 Data Compression Conference (DCC) Pub Date : 2019-03-26 DOI: 10.1109/DCC.2019.00065

Hadi Amirpour, A. Pinheiro, Manuela Pereira, Fernando Lopes, M. Ghanbari

引用次数: 12