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2007 Data Compression Conference (DCC'07)最新文献

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Data Hiding based Compression Mechanism for 3D Models 基于数据隐藏的3D模型压缩机制
2007 Data Compression Conference (DCC'07) Pub Date : 2007-03-27 DOI: 10.1109/DCC.2007.30
Hui Li, Parag Agarwal, B. Prabhakaran
{"title":"Data Hiding based Compression Mechanism for 3D Models","authors":"Hui Li, Parag Agarwal, B. Prabhakaran","doi":"10.1109/DCC.2007.30","DOIUrl":"https://doi.org/10.1109/DCC.2007.30","url":null,"abstract":"Different compression methods (Jingliang Peng et al., 2005) such as progressive meshes and single refinement mesh compression exist for mesh representation for 3D models and improving them is a challenge. This paper is a step in this direction, where we show that data hiding methods can be used to significantly improve the compression achieved for such methods. 3D meshes are made up of connectivity (edge set E) and geometric (vertices set V) information. The data hiding method should provide a very high embedding rate in order to achieve a desirable compression ratio. This can be modeled mathematically, given 'V points or vertices in 3D space; for a given compression ratio we use 'AT' points and hide rest of the connectivity and geometric information inside it. These points are termed as the encoding points and the encoded information is termed is the compressed information.","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127778553","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
Hyperspectral Image Compression with Optimization for Spectral Analysis 基于光谱分析优化的高光谱图像压缩
2007 Data Compression Conference (DCC'07) Pub Date : 2007-03-27 DOI: 10.1109/DCC.2007.46
Kameron Romines, E. S. Hong
{"title":"Hyperspectral Image Compression with Optimization for Spectral Analysis","authors":"Kameron Romines, E. S. Hong","doi":"10.1109/DCC.2007.46","DOIUrl":"https://doi.org/10.1109/DCC.2007.46","url":null,"abstract":"Hyperspectral imaging is of interest in a large number of remote sensing applications, such as geology and pollution monitoring, in order to detect and analyze surface and atmospheric composition. The processing of these images, called spectral analysis, allows for the identification of the specific mineralogical and agricultural elements which compose an image. We seek to understand how loss due to compression can affect the spectral analysis results, and then modify the compression algorithms to improve spectral analysis performance. More specifically, we suggest modifications to the 3D-SPIHT algorithm for improving the classification accuracy of hyperspectral images for two classification techniques: spectral angle mapper (SAM) and matched filtering (MF). Results of our modification show an improvement in the error rate as reported by the classification techniques, indicating an increase in the ability to analyze hyperspectral images which have been compressed.","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130197454","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
Four-Dimensional Wavelet Compression of 4-D Medical Images Using Scalable 4-D SBHP 基于可伸缩四维shbhp的四维医学图像小波压缩
2007 Data Compression Conference (DCC'07) Pub Date : 2007-03-27 DOI: 10.1109/DCC.2007.39
Y. Liu, W. Pearlman
{"title":"Four-Dimensional Wavelet Compression of 4-D Medical Images Using Scalable 4-D SBHP","authors":"Y. Liu, W. Pearlman","doi":"10.1109/DCC.2007.39","DOIUrl":"https://doi.org/10.1109/DCC.2007.39","url":null,"abstract":"This paper proposes a low-complexity wavelet-based method for progressive lossy-to-lossless compression of four dimensional (4-D) medical images. The subband block hierarchal partitioning (SBHP) algorithm is modified and extended to four dimensions, and applied to every code block independently. The resultant algorithm, 4D-SBHP, efficiently encodes 4D image data by the exploitation of the dependencies in all dimensions, while enabling progressive SNR and resolution decompression. The resolution scalable and lossy-to-lossless performances are empirically investigated. The experimental results show that our 4-D scheme achieves better compression performance on 4-D medical images when compared with 3-D volumetric compression schemes","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131186972","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: 20
A Stochastic Model for Video and its Information Rates 视频及其信息率的随机模型
2007 Data Compression Conference (DCC'07) Pub Date : 2007-03-27 DOI: 10.1109/DCC.2007.8
A. L. Cunha, M. Do, M. Vetterli
{"title":"A Stochastic Model for Video and its Information Rates","authors":"A. L. Cunha, M. Do, M. Vetterli","doi":"10.1109/DCC.2007.8","DOIUrl":"https://doi.org/10.1109/DCC.2007.8","url":null,"abstract":"We propose a stochastic model for video and compute its information rates. The model has two sources of information representing ensembles of camera motion and visual scene data (i.e. \"realities\"). The sources of information are combined generating a vector process that we study in detail. Both lossless and lossy information rates are derived. The model is further extended to account for realities that change over time. We derive bounds on the lossless and lossy information rates for this dynamic reality model, stating conditions under which the bounds are tight. Experiments with synthetic sources suggest that in the presence of scene motion, simple hybrid coding using motion estimation with DPCM can be suboptimal relative to the true rate-distortion bound","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123797522","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
Differential Compression of Executable Code 可执行代码的差分压缩
2007 Data Compression Conference (DCC'07) Pub Date : 2007-03-27 DOI: 10.1109/DCC.2007.32
G. Motta, J. Gustafson, Samson Chen
{"title":"Differential Compression of Executable Code","authors":"G. Motta, J. Gustafson, Samson Chen","doi":"10.1109/DCC.2007.32","DOIUrl":"https://doi.org/10.1109/DCC.2007.32","url":null,"abstract":"A platform-independent algorithm to compress file differences is presented here. Since most file updates consist of software updates and security patches, particular attention is dedicated to making this algorithm suitable to efficient compression of differences between executable files. This algorithm is designed so that its low-complexity decoder can be used in mobile and embedded devices. Compression is compared with several existing methods on a common test suite","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133627265","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: 15
Texture Classification Using VQ with Feature Extraction based on Transforms Motivated by the Human Visual System 基于视觉变换的VQ纹理分类与特征提取
2007 Data Compression Conference (DCC'07) Pub Date : 2007-03-27 DOI: 10.1109/DCC.2007.74
A. D. Lillo, J. Storer, G. Motta
{"title":"Texture Classification Using VQ with Feature Extraction based on Transforms Motivated by the Human Visual System","authors":"A. D. Lillo, J. Storer, G. Motta","doi":"10.1109/DCC.2007.74","DOIUrl":"https://doi.org/10.1109/DCC.2007.74","url":null,"abstract":"The textured images are classified with a supervised segmentation algorithm (the classifier is trained first on texture samples). Texture features are extracted in the frequency domain and classified by a vector quantizer. Since feature vectors are computed and classified independently, for each pixel, a Kuwahara-like filter is used on the final classification to improve consistency. Feature vectors are computed by taking a 2D Fourier transform of a window centered on a pixel; the phase is discarded, while the magnitude of the transform is retained and mapped to polar coordinates. The polar mapping improves the precision of the classifier on the test problems. Principal component analysis is used to compact the feature vector and contain the complexity of the vector quantizer used to select a small number of representative signatures for each class. The training yields a small codebook associated with each texture image of the training set","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131765879","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
Exploiting Prior Knowledge in The Recovery of Signals from Noisy Random Projections 利用先验知识从噪声随机投影中恢复信号
2007 Data Compression Conference (DCC'07) Pub Date : 2007-03-27 DOI: 10.1109/DCC.2007.37
J. Garcia-Frías, I. Esnaola
{"title":"Exploiting Prior Knowledge in The Recovery of Signals from Noisy Random Projections","authors":"J. Garcia-Frías, I. Esnaola","doi":"10.1109/DCC.2007.37","DOIUrl":"https://doi.org/10.1109/DCC.2007.37","url":null,"abstract":"It has been recently shown that if a, signal can be compressed in some basis, then it can be reconstructed in such basis from, a certain number of random, projections. By allowing additional distortion, this holds even if the projections are corrupted by noise. We extend this result by showing that it is possible to exploit prior knowledge (e.g., if the signal is a realization of a stochastic process,) to significantly improve reconstruction performance. This is done in a fashion resembling standard joint source-channel coding of digital sources. Moreover, the exploitation of such knowledge allows for reconstruction in bases where the signal is not sparse","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128072417","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
On Multi-Stage Sequential Coding of Correlated Sources 相关信源的多阶段顺序编码
2007 Data Compression Conference (DCC'07) Pub Date : 2007-03-27 DOI: 10.1109/DCC.2007.62
Jia Wang, Xiaolin Wu, Jun Sun, Songyu Yu
{"title":"On Multi-Stage Sequential Coding of Correlated Sources","authors":"Jia Wang, Xiaolin Wu, Jun Sun, Songyu Yu","doi":"10.1109/DCC.2007.62","DOIUrl":"https://doi.org/10.1109/DCC.2007.62","url":null,"abstract":"We study the problem of multi-stage sequential coding (MSSC), which is an extension of sequential coding of correlated sources. Consider two correlated random variables X and Y to be coded in two stages. The first stage is sequential coding as referred to in the existing literature. At the second stage, the Y encoder refines the information of Y without any knowledge of X, and X encoder refines the information of X with the knowledge of Y, while all previous outputs are known at the decoder. As the sequential coding problem provides a theoretical abstraction of video coding, the MSSC model is a theoretical abstraction of scalable video coding, which is an important application of network communications. We give an achievable region for the MSSC system. The given achievable region is tight when Y is required to be reconstructed perfectly in the usual Shannon sense at the second stage. We also study the minimum total rate MSSC problem, and derive the minimum total rate for Gaussian sources. This result disproves the possibility that the minimum total rate of one stage sequential coding can be achieved at both stages even for correlated Gaussian sources. Thus we offer a theoretical explanation for the performance loss of scalable video coding widely noted by practitioners","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129103303","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
Bounds to the Rate Distortion Tradeoff of the Binary Markov Source 二元马尔可夫源的率失真折衷的界限
2007 Data Compression Conference (DCC'07) Pub Date : 2007-03-27 DOI: 10.1109/DCC.2007.20
D. Vasudevan
{"title":"Bounds to the Rate Distortion Tradeoff of the Binary Markov Source","authors":"D. Vasudevan","doi":"10.1109/DCC.2007.20","DOIUrl":"https://doi.org/10.1109/DCC.2007.20","url":null,"abstract":"We provide bounds to the rate distortion tradeoff of the binary Markov source with the Hamming distance as the distortion measure. The tradeoff has been completely characterized by Gray (1970) for distortions less than a critical value Dc. Our motivation is to examine the tradeoff for values of distortion above Dc. Our inner bound to the tradeoff follows from an achievable scheme that uses conditional codebooks based on decision feedback at the encoder. Our outer bound follows from an extension of the technique of Berger (1977)","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132454431","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
Bit Recycling with Prefix Codes 前缀码的位回收
2007 Data Compression Conference (DCC'07) Pub Date : 2007-03-27 DOI: 10.1109/DCC.2007.18
Danny Dubé, V. Beaudoin
{"title":"Bit Recycling with Prefix Codes","authors":"Danny Dubé, V. Beaudoin","doi":"10.1109/DCC.2007.18","DOIUrl":"https://doi.org/10.1109/DCC.2007.18","url":null,"abstract":"This paper presents a technique that aims at reducing the expansion of the compressed files that is caused by the multiplicity of equivalent messages. It does not try to eliminate multiplicity. Instead, it takes advantage of multiplicity by converting it into useful information, which we choose to describe parts of the compressed file itself. We call this technique bit recycling. On the decompressor side, when a message M is received, the set M of messages equivalent to M is determined, and the particular choice (M Sigma M) made by the compressor is perceived as a hint, which translates into a bit sequence. Such a bit sequence is said to be recycled and the bits it contains can be omitted from the compressed file. On the compressor side, the task is more complicated because the message that is currently selected among the set of equivalent ones carries information about the following messages. To make these far- reaching selections, the compressor may use non-deterministic choices but we propose a resolution algorithm along with a greedy version that allows the compressor to proceed in a stream-like fashion. We propose two ways to obtain recycled bit sequences: flat recycling, where a constant number of bits (about log2 M) is recovered for any selection of M Sigma M; and proportional recycling, where the number of bits that is recovered for the selection of M Sigma M grows with the cost of encoding M. In a 2006 paper, Dube and Beaudoin showed that they obtained the best experimental results using proportional recycling. We believe this recycling method to be close to optimal.","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128754773","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
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