We propose a Compressed Sensing application to audio signals and analyze its audio perceptual quality with PEAQ.
提出了一种音频信号的压缩感知应用，并利用PEAQ分析了其音频感知质量。
{"title":"Lossy Audio Compression via Compressed Sensing","authors":"Rubem J. V. de Medeiros, E. Gurjão, J. Carvalho","doi":"10.1109/DCC.2010.88","DOIUrl":"https://doi.org/10.1109/DCC.2010.88","url":null,"abstract":"We propose a Compressed Sensing application to audio signals and analyze its audio perceptual quality with PEAQ.","PeriodicalId":299459,"journal":{"name":"2010 Data Compression Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129109082","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}
Intra picture coding plays an important role in video coding algorithms. In this paper, we investigate the pixel spatial correlation in HD picture and propose a macroblock level horizontal spatial prediction(HSP) based intra coding method. Because the pixels have the absolutely stronger correlation in horizontal direction than that in the vertical direction, each macroblock will try to be divided into left and right partitions. The right partition will be encoded with the conventional intra mode and then the reconstruction of it will be used to predict the left partition. The strong correlation between the right and left will contribute to the left partition significantly, and the encoding efficiency can be improved for the intra macroblock. With the decision of RDO, about 30-60% macroblocks will benefit from the HSP based intra coding. The experimental results show that the proposed intra coding scheme can improve the encoding efficiency with 0.17dB in average and has the potential to be further improved.
{"title":"Horizontal Spatial Prediction for High Dimension Intra Coding","authors":"Pin Tao, Wenting Wu, Chao Wang, Mou Xiao, Jiangtao Wen","doi":"10.1109/DCC.2010.76","DOIUrl":"https://doi.org/10.1109/DCC.2010.76","url":null,"abstract":"Intra picture coding plays an important role in video coding algorithms. In this paper, we investigate the pixel spatial correlation in HD picture and propose a macroblock level horizontal spatial prediction(HSP) based intra coding method. Because the pixels have the absolutely stronger correlation in horizontal direction than that in the vertical direction, each macroblock will try to be divided into left and right partitions. The right partition will be encoded with the conventional intra mode and then the reconstruction of it will be used to predict the left partition. The strong correlation between the right and left will contribute to the left partition significantly, and the encoding efficiency can be improved for the intra macroblock. With the decision of RDO, about 30-60% macroblocks will benefit from the HSP based intra coding. The experimental results show that the proposed intra coding scheme can improve the encoding efficiency with 0.17dB in average and has the potential to be further improved.","PeriodicalId":299459,"journal":{"name":"2010 Data Compression Conference","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131587081","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}
A Wyner-Ziv Quantizer design method is introduced when the indices at the output of the encoder are transmitted over a noisy channel. The source encoder is considered as a scalar Lloyd quantizer followed by a binning and an index assignment (BIA) mapping. A modified simulated annealing based algorithm is used for BIA mapping design. A minimax solution for Wyner-Ziv problem under channel mismatch condition is also suggested when the channel is assumed to be binary symmetric channel and no information about the statistic of channel is available except the range of bit error rate. Finally the simulation results are presented which show the effectiveness of the proposed algorithm over other common alternative approaches. These results approve the proposed minimax solution too.
{"title":"Scalar Quantizer Design for Noisy Channel with Decoder Side Information","authors":"Sepideh Shamaie, F. Lahouti","doi":"10.1109/DCC.2010.91","DOIUrl":"https://doi.org/10.1109/DCC.2010.91","url":null,"abstract":"A Wyner-Ziv Quantizer design method is introduced when the indices at the output of the encoder are transmitted over a noisy channel. The source encoder is considered as a scalar Lloyd quantizer followed by a binning and an index assignment (BIA) mapping. A modified simulated annealing based algorithm is used for BIA mapping design. A minimax solution for Wyner-Ziv problem under channel mismatch condition is also suggested when the channel is assumed to be binary symmetric channel and no information about the statistic of channel is available except the range of bit error rate. Finally the simulation results are presented which show the effectiveness of the proposed algorithm over other common alternative approaches. These results approve the proposed minimax solution too.","PeriodicalId":299459,"journal":{"name":"2010 Data Compression Conference","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132909765","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}
This paper presents a method for improving wavelet-based Compressed Sensing (CS) reconstruction algorithms by exploiting the dependencies among wavelet coefficients. During CS recovery, a simple measure of significance for each wavelet coefficient is calculated using a weighted sum of the (estimated) magnitudes of the wavelet coefficient, its highly correlated neighbors, and parent. This simple measure is incorporated into three CS recovery algorithms, Reweighted L1 minimization algorithms (RL1), Iteratively Reweighted Least Squares (IRLS), and Iterative Hard Thresholding (IHT). Experimental results using one-dimensional signals and images illustrate that the proposed method (i) improves reconstruction quality for a given number of measurements, (ii) requires fewer measurements for a desired reconstruction quality, and (iii) significantly reduces reconstruction time.
{"title":"Exploiting Wavelet-Domain Dependencies in Compressed Sensing","authors":"Yookyung Kim, M. Nadar, A. Bilgin","doi":"10.1109/DCC.2010.51","DOIUrl":"https://doi.org/10.1109/DCC.2010.51","url":null,"abstract":"This paper presents a method for improving wavelet-based Compressed Sensing (CS) reconstruction algorithms by exploiting the dependencies among wavelet coefficients. During CS recovery, a simple measure of significance for each wavelet coefficient is calculated using a weighted sum of the (estimated) magnitudes of the wavelet coefficient, its highly correlated neighbors, and parent. This simple measure is incorporated into three CS recovery algorithms, Reweighted L1 minimization algorithms (RL1), Iteratively Reweighted Least Squares (IRLS), and Iterative Hard Thresholding (IHT). Experimental results using one-dimensional signals and images illustrate that the proposed method (i) improves reconstruction quality for a given number of measurements, (ii) requires fewer measurements for a desired reconstruction quality, and (iii) significantly reduces reconstruction time.","PeriodicalId":299459,"journal":{"name":"2010 Data Compression Conference","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128181571","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}
For a class of low-density parity-check (LDPC) code ensembles with right node degrees as binomial distribution, this paper proves that the theoretically optimal LDPC code ensemble should be regular for a binary-symmetric channel (BSC) and Gallager’s decoding algorithm A. Our proof consists of two steps. First, with the assumption of right edge degrees as binomial, we prove that the LDPC threshold of single left edge degree is larger than that of multiple left edge degrees. Second, we verify that the LDPC threshold is the largest when binomial distribution of right node degrees degrades to single value. Very interestingly, although both right and left edge degrees are unique in the theoretically optimal LDPC code ensemble, they are floating values. When the floating degrees are approximated by a two-term binomial distribution, the threshold at half rate is exactly the same as Bazzi’s result via linear programming. It verifies our proof from another angle
{"title":"Theoretically Optimal Low-Density Parity-Check Code Ensemble for Gallager's Decoding Algorithm A","authors":"Feng Wu, Peiwen Yu","doi":"10.1109/DCC.2010.84","DOIUrl":"https://doi.org/10.1109/DCC.2010.84","url":null,"abstract":"For a class of low-density parity-check (LDPC) code ensembles with right node degrees as binomial distribution, this paper proves that the theoretically optimal LDPC code ensemble should be regular for a binary-symmetric channel (BSC) and Gallager’s decoding algorithm A. Our proof consists of two steps. First, with the assumption of right edge degrees as binomial, we prove that the LDPC threshold of single left edge degree is larger than that of multiple left edge degrees. Second, we verify that the LDPC threshold is the largest when binomial distribution of right node degrees degrades to single value. Very interestingly, although both right and left edge degrees are unique in the theoretically optimal LDPC code ensemble, they are floating values. When the floating degrees are approximated by a two-term binomial distribution, the threshold at half rate is exactly the same as Bazzi’s result via linear programming. It verifies our proof from another angle","PeriodicalId":299459,"journal":{"name":"2010 Data Compression Conference","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128200541","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}
We consider the source coding problem with side information. Especially, we consider the FV code in the case that the encoder and the decoder can see side information. We obtain the condition that there exists a FV code under the condition that the overflow probability is smaller than or equal to some constant.
{"title":"On the Overflow Probability of Fixed-to-Variable Length Codes with Side Information","authors":"R. Nomura, T. Matsushima","doi":"10.1109/DCC.2010.93","DOIUrl":"https://doi.org/10.1109/DCC.2010.93","url":null,"abstract":"We consider the source coding problem with side information. Especially, we consider the FV code in the case that the encoder and the decoder can see side information. We obtain the condition that there exists a FV code under the condition that the overflow probability is smaller than or equal to some constant.","PeriodicalId":299459,"journal":{"name":"2010 Data Compression Conference","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129352323","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}
We introduce a systematic distributed quantizer design method, called {it{localization}}, in which, out of an existing centralized (global) quantizer, one synthesizes the distributed (local) quantizer using high-rate scalar quantization combined with entropy coding. The general localization procedure is presented, along with a practical application to a quantized beamforming problem for multiple-input multiple-output broadcast channels. For our particular application, not only localization provides high performance distributed quantizers with very low feedback rates, but also reveals an interesting property of finite rate feedback schemes that might be of theoretical interest: For single-user multiple-input single-output systems, one can achieve the performance of almost any quantized beamforming scheme with an arbitrarily low feedback rate, when the transmitter power is sufficiently large.
{"title":"A Systematic Distributed Quantizer Design Method with an Application to MIMO Broadcast Channels","authors":"Erdem Koyuncu, H. Jafarkhani","doi":"10.1109/DCC.2010.34","DOIUrl":"https://doi.org/10.1109/DCC.2010.34","url":null,"abstract":"We introduce a systematic distributed quantizer design method, called {it{localization}}, in which, out of an existing centralized (global) quantizer, one synthesizes the distributed (local) quantizer using high-rate scalar quantization combined with entropy coding. The general localization procedure is presented, along with a practical application to a quantized beamforming problem for multiple-input multiple-output broadcast channels. For our particular application, not only localization provides high performance distributed quantizers with very low feedback rates, but also reveals an interesting property of finite rate feedback schemes that might be of theoretical interest: For single-user multiple-input single-output systems, one can achieve the performance of almost any quantized beamforming scheme with an arbitrarily low feedback rate, when the transmitter power is sufficiently large.","PeriodicalId":299459,"journal":{"name":"2010 Data Compression Conference","volume":"329 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133498802","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}
A Layered Depth Image (LDI) is one of the popular representation and rendering methods for 3D objects with complex geometries. In this paper, we propose the new compression algorithm for depth information of a 3D object represented by LDI. For the purpose, we introduce the concept of partial surfaces to seek highly correlated depth data irrespective of their layer and derive a depth compression algorithm by using them. Partial surfaces are approximated by a Bézier patch and residual information is encoded by a shape-adaptive transform. Experimental results show that our proposed compression method achieves a better compression performance than any other previous methods.
{"title":"Depth Compression of 3D Object Represented by Layered Depth Image","authors":"Sang-Young Park, Seong-Dae Kim","doi":"10.1109/DCC.2010.50","DOIUrl":"https://doi.org/10.1109/DCC.2010.50","url":null,"abstract":"A Layered Depth Image (LDI) is one of the popular representation and rendering methods for 3D objects with complex geometries. In this paper, we propose the new compression algorithm for depth information of a 3D object represented by LDI. For the purpose, we introduce the concept of partial surfaces to seek highly correlated depth data irrespective of their layer and derive a depth compression algorithm by using them. Partial surfaces are approximated by a Bézier patch and residual information is encoded by a shape-adaptive transform. Experimental results show that our proposed compression method achieves a better compression performance than any other previous methods.","PeriodicalId":299459,"journal":{"name":"2010 Data Compression Conference","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129423666","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}
This paper examines the non-zero pulse position amplitude quantization implicit in algebraic codebook code-excited linear prediction speech coding. It is demonstrated that the quantization used in ACELP is effective in a rate distortion sense at the typical encoding rates commonly used.
{"title":"Analysis of Amplitude Quantization in ACELP Excitation Coding","authors":"W. Patchoo, T. Fischer, Changho Ahn, Sangwon Kang","doi":"10.1109/DCC.2010.52","DOIUrl":"https://doi.org/10.1109/DCC.2010.52","url":null,"abstract":"This paper examines the non-zero pulse position amplitude quantization implicit in algebraic codebook code-excited linear prediction speech coding. It is demonstrated that the quantization used in ACELP is effective in a rate distortion sense at the typical encoding rates commonly used.","PeriodicalId":299459,"journal":{"name":"2010 Data Compression Conference","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133989330","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}
We study information theoretical performance of common video coding methodologies at the frame level. Via an abstraction of consecutive video frames as correlated random variables, many existing video coding techniques, including the baseline of MPEG-x and H.26x, the scalable coding and the distributed video coding, can have corresponding information theoretical models. The theoretical achievable rate distortion regions have been completely solved for some systems while for others remain open. We show that the achievable rate region of sequential coding equals to that of predictive coding for Markov sources. We give a theoretical analysis of the coding efficiency of B frames in the popular hybrid video coding architecture, bringing new understanding of the current practice. We also find that distributed sequential video coding generally incurs a performance loss if the source is not Markov.
{"title":"Information Flows in Video Coding","authors":"Jia Wang, Xiaolin Wu","doi":"10.1109/DCC.2010.21","DOIUrl":"https://doi.org/10.1109/DCC.2010.21","url":null,"abstract":"We study information theoretical performance of common video coding methodologies at the frame level. Via an abstraction of consecutive video frames as correlated random variables, many existing video coding techniques, including the baseline of MPEG-x and H.26x, the scalable coding and the distributed video coding, can have corresponding information theoretical models. The theoretical achievable rate distortion regions have been completely solved for some systems while for others remain open. We show that the achievable rate region of sequential coding equals to that of predictive coding for Markov sources. We give a theoretical analysis of the coding efficiency of B frames in the popular hybrid video coding architecture, bringing new understanding of the current practice. We also find that distributed sequential video coding generally incurs a performance loss if the source is not Markov.","PeriodicalId":299459,"journal":{"name":"2010 Data Compression Conference","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121916852","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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