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Approximating Rate-Distortion Graphs of Individual Data: Experiments in Lossy Compression and Denoising [article]

Steven de Rooij, Paul Vitanyi
2006 arXiv   pre-print
To apply the theory we approximate the Kolmogorov complexity by standard data compression techniques, and perform a number of experiments with lossy compression and denoising of objects from different  ...  Instead, we analyze rate-distortion properties of individual objects using the recently developed algorithmic rate-distortion theory.  ...  Denoising For each denoising experiment, we report a number of important objects, a graph that shows the approximate distortion-rate function and a graph that shows the approximate codelength function.  ... 
arXiv:cs/0609121v1 fatcat:yfjuemmyv5es5gpylvcy46znni

Approximating Rate-Distortion Graphs of Individual Data: Experiments in Lossy Compression and Denoising

Steven de Rooij, Paul Vitanyi
2012 IEEE transactions on computers  
To apply the theory we approximate the Kolmogorov complexity by standard data compression techniques, and perform a number of experiments with lossy compression and denoising of objects from different  ...  Instead, we analyze rate-distortion properties of individual objects using the recently developed algorithmic rate-distortion theory.  ...  Denoising For each denoising experiment, we report a number of important objects, a graph that shows the approximate distortion-rate function and a graph that shows the approximate code length function  ... 
doi:10.1109/tc.2011.25 fatcat:nxgenw27bbeadbkaeq5gj54m3y

Lossy compression of scientific spacecraft data using wavelets. Application to the CASSINI spacecraft data compression

L. Belmon, H. Benoit-Cattin, A. Baskurt, J.-L. Bougeret
2002 Astronomy and Astrophysics  
This paper presents a lossy coding scheme designed to be board on the Cassini spacecraft which has been launched in 1997 to study Saturn planet.  ...  To deal with specific time-frequency data and numerous constraints, our coding algorithm is based on wavelet decomposition associated to an adaptive bit allocation procedure.  ...  Introduction The need for lossy compression in spacecraft data transmission has been growing in the last ten years consequently with the increasing number of space exploration missions.  ... 
doi:10.1051/0004-6361:20020225 fatcat:ibiya34cbbdavobfrcni6rboyy

Improved Statistically Based Retrievals via Spatial-Spectral Data Compression for IASI Data

Joaquin Garcia-Sobrino, Valero Laparra, Joan Serra-Sagrista, Xavier Calbet, Gustau Camps-Valls
2019 IEEE Transactions on Geoscience and Remote Sensing  
In this paper we analyze the effect of spatial and spectral compression on the performance of statistically based retrieval.  ...  These experiments suggest that compression can be understood as an indirect way to regularize the data and exploit spatial neighbours information, which improves the performance of pixel-wise statistics  ...  Lossy compression is known to be an indirect way of performing signal filtration and denoising.  ... 
doi:10.1109/tgrs.2019.2901396 fatcat:7jzygmj56rb5jne7ov5oh6emri

Rate Distortion and Denoising of Individual Data Using Kolmogorov Complexity

Nikolai K. Vereshchagin, Paul M.B. Vitanyi
2010 IEEE Transactions on Information Theory  
) and this suggests an approach to denoising.  ...  Examples are given of list distortion, Hamming distortion, and Euclidean distortion. The algorithmic rate-distortion function can behave differently from Shannon's rate-distortion function.  ...  Muchnik gave the probabilistic proof of Claim 4 in Remark 9 after having seen the deterministic proof. Such a probabilistic proof was independently proposed by M. Koucký.  ... 
doi:10.1109/tit.2010.2048491 fatcat:wyjuj3cntraczi4u4flil6csk4

Rate Distortion and Denoising of Individual Data Using Kolmogorov complexity [article]

Nikolai K. Vereshchagin, Paul M.B. Vitanyi (CWI, University of Amsterdam)
2009 arXiv   pre-print
) and this suggests an approach to denoising; and, finally, we show that the different behavior of the rate-distortion curves of individual source words to some extent disappears after averaging over the  ...  Examples are given of list distortion, Hamming distortion, and Euclidean distortion. The algorithmic rate-distortion function can behave differently from Shannon's rate-distortion function.  ...  Muchnik gave the probabilistic proof of Claim 4 in Remark 9 after having seen the deterministic proof. Such a probabilistic proof was independently proposed by Michal Koucký.  ... 
arXiv:cs/0411014v4 fatcat:jc47o5fkh5dxnozpjsoz4stj3m

Similarity and denoising

P. M. B. Vitanyi
2012 Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences  
The point of best denoising can be deduced from the first graph, where it is the point where the distortion-rate curve sharply levels off.  ...  We approximated the distortion-rate function of a noiseless cross called the target.  ... 
doi:10.1098/rsta.2012.0091 pmid:23277611 fatcat:7pzzf3vjbjgqbb5v2l6sawe7ty

Optimized Vector Quantization For Bayer Color Filter Array

M. Lakshmi, J. Senthil Kumar
2015 Zenodo  
Captured data is interpolated into a full color image and compressed in applications. Color interpolation before compression leads to data redundancy.  ...  Color Filter Array (CFA) in digital cameras permits only one of the three primary (red-green-blue) colors to be sensed in a pixel and interpolates the two missing components through a method named demosaicking  ...  Large dimension vectors produce transparency in quantization at a specific bit-rate chosen. In VQ, data is quantized as contiguous blocks called vectors instead of individual samples.  ... 
doi:10.5281/zenodo.1109805 fatcat:buwm2afvsfe7npfed46pbwputq

Standard and Specific Compression Techniques for DNA Microarray Images

Miguel Hernández-Cabronero, Ian Blanes, Michael W. Marcellin, Joan Serra-Sagristà
2012 Algorithms  
We review the state of the art in DNA microarray image compression and provide original comparisons between standard and microarray-specific compression techniques that validate and expand previous work  ...  In a set of experiments conducted for this paper, we obtain new results for several popular image coding techniques that include the most recent coding standards.  ...  The role of data compression in computational biology and the state of the art has been addressed by several authors [4, 5] . Both lossy and lossless techniques have been proposed in the literature.  ... 
doi:10.3390/a5010030 fatcat:nvkg7jyojjatvjaw5yoxp4a4tq

Lossy Compression of Dynamic, Weighted Graphs

Wilko Henecka, Matthew Roughan
2015 2015 3rd International Conference on Future Internet of Things and Cloud  
In this paper we present a method aimed at lossy compression of large, dynamic, weighted graphs.  ...  A graph is used to represent data in which the relationships between the objects in the data are at least as important as the objects themselves.  ...  Experiment The generic structure of our experiments in as follows: Generate ⇒ Measure ⇒ Approximate.  ... 
doi:10.1109/ficloud.2015.64 dblp:conf/ficloud/HeneckaR15 fatcat:udwvzbgiundkreiywd4p4wl56i

Distributed correlated data gathering in wireless sensor networks via compressed sensing

Markus Leinonen, Marian Codreanu, Markku Juntti
2013 2013 Asilomar Conference on Signals, Systems and Computers  
The method is shown to achieve higher distortion-rate performance than the baselines and to enable a trade-off between compression performance and encoding complexity via the pre-quantization of measurements  ...  The objective of this thesis is to develop and analyze energy-efficient distributed compressed data acquisition techniques for WSNs.  ...  Rate-distortion performance of lossy compressed sensing This chapter addresses the rate-distortion (RD) performance of lossy CS from an information-theoretic perspective.  ... 
doi:10.1109/acssc.2013.6810310 dblp:conf/acssc/LeinonenCJ13 fatcat:wdpvzue3wzcklpfsevkr7uwvmm

A Study of Image Pre-processing for Faster Object Recognition [article]

Md Tanzil Shahriar, Huyue Li
2020 arXiv   pre-print
Quality of image always plays a vital role in in-creasing object recognition or classification rate.  ...  It is more difficult to extract features from such unprocessed images which in-turn reduces object recognition or classification rate.  ...  Data compression can be either lossless or lossy, and intuitively speaking, lossy methods tend to have better compression ratios. And VR transform is a lossy compression.  ... 
arXiv:2011.06928v1 fatcat:3mloskte3rd6pc6qdgqmepytv4

Custom Design of JPEG Quantisation Tables for Compressing Iris Polar Images to Improve Recognition Accuracy [chapter]

Mario Konrad, Herbert Stögner, Andreas Uhl
2009 Lecture Notes in Computer Science  
Superior matching results in iris recognition in terms of average Hamming distance and improved ROC are found as compared to the use of the default JPEG quantisation table.  ...  Custom JPEG quantisation matrices are proposed to be used in the context of compressing iris polar images within iris recognition.  ...  Acknowledgements Most of the work described in this paper has been done in the scope of the "Project I Lab" in the master program on "Communication Engineering for IT" at Carinthia Tech Institute.  ... 
doi:10.1007/978-3-642-01793-3_110 fatcat:gh4bxsnpbbaz3fnloauvctdt5i

Learning of Graph Compressed Dictionaries for Sparse Representation Classification

Farshad Nourbakhsh, Eric Granger
2016 Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods  
Despite the limited target data available to design face models in video surveillance applications, many faces of non-target individuals may be captured in operational environments, and over multiple cameras  ...  Graph factorization compression has been shown to efficiently compress data, and can therefore rapidly construct compressed dictionaries.  ...  In our experiment, the size of external data is increased in each experiment by randomly selecting the data from 60 individuals that starts from 1 to 15 individuals for ESRC and RADL wo .  ... 
doi:10.5220/0005710403090316 dblp:conf/icpram/NourbakhshG16 fatcat:vpnv6fc245ciditfzje2vost3y

Message-Passing De-Quantization With Applications to Compressed Sensing

U. S. Kamilov, V. K. Goyal, S. Rangan
2012 IEEE Transactions on Signal Processing  
GAMP is a recently-developed class of algorithms that uses Gaussian approximations in belief propagation and allows arbitrary separable input and output channels.  ...  Non-regular quantization is empirically demonstrated to greatly improve rate-distortion performance in some problems with oversampling or with undersampling combined with a sparsity-inducing prior.  ...  It arises both from the discretization in digital acquisition devices and the quantization performed for lossy compression.  ... 
doi:10.1109/tsp.2012.2217334 fatcat:qusxkijqcvctjiph22qph3kfp4
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