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In-Depth Exploration of Single-Snapshot Lossy Compression Techniques for N-Body Simulations [article]

Dingwen Tao, Sheng Di, Zizhong Chen, Franck Cappello
2017 arXiv   pre-print
We design a series of novel optimization techniques based on the two representative real-world N-body simulation codes.  ...  In situ lossy compression allowing user-controlled data loss can significantly reduce the I/O burden.  ...  EXPLORATION OF OPTIMIZATIONS FOR LOSSY COMPRESSION ON N-BODY SIMULATION DATA SETS In this section, we first discuss prediction models for lossy compression on N-body simulation data sets and optimize the  ... 
arXiv:1711.03888v1 fatcat:gva3gkabcfgfli3p6kcw3uxqb4

Improving Inference for Neural Image Compression [article]

Yibo Yang, Robert Bamler, Stephan Mandt
2021 arXiv   pre-print
We consider the problem of lossy image compression with deep latent variable models.  ...  We propose remedies for each of these three limitations based on ideas related to iterative inference, stochastic annealing for discrete optimization, and bits-back coding, resulting in the first application  ...  This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under Contract No. HR001120C0021.  ... 
arXiv:2006.04240v4 fatcat:2c45ftyttfacfdwfmu3pshjqfi

Survey of Hybrid Image Compression Techniques

Emy Setyaningsih, Agus Harjoko
2017 International Journal of Electrical and Computer Engineering (IJECE)  
This technique combines lossy and lossless compression method to obtain a high-quality compression ratio while maintaining the quality of the reconstructed image.  ...  This paper presents a survey of research papers discussing improvement of various hybrid compression techniques during the last decade.  ...  CONCLUSION The improvement of image compression technique to get an optimal compression ratio and best quality of the image can be made by combining lossy and lossless compression technique known as a  ... 
doi:10.11591/ijece.v7i4.pp2206-2214 fatcat:in5g6jpjqzdztbaqq5d2zo5bzy

Optimizing Lossy Compression Rate-Distortion from Automatic Online Selection between SZ and ZFP [article]

Dingwen Tao, Sheng Di, Xin Liang, Zizhong Chen, Franck Cappello
2019 arXiv   pre-print
In this paper, the automatic selection optimizes the rate-distortion, an important statistical quality metric based on the signal-to-noise ratio.  ...  We then propose an efficient online, low-overhead selection algorithm that predicts the compression quality accurately for two compressors in early processing stages and selects the best-fit compressor  ...  be improved significantly for that application?  ... 
arXiv:1806.08901v2 fatcat:wxujbiwfqve23ooedoifk627la

Hybrid Approaches to Image Coding: A Review

Rehna V, Jeya Kumar.
2011 International Journal of Advanced Computer Science and Applications  
Practically efficient compression systems based on hybrid coding which combines the advantages of different traditional methods of image coding have also being developed over the years.  ...  Literature on hybrid techniques of image coding over the past years is also reviewed. An attempt is made to highlight the neuro-wavelet approach for enhancing coding efficiency.  ...  compression system based on the neuro-wavelet model TABLE I .  ... 
doi:10.14569/ijacsa.2011.020716 fatcat:lpin6okdyrgkhkmdkoqgpxs7nq

Hybrid Approaches to Image Coding: A Review [article]

Rehna. V. J, Jeyakumar. M. K
2012 arXiv   pre-print
Practically efficient compression systems based on hybrid coding which combines the advantages of different traditional methods of image coding have also been developed over the years.  ...  Literature on hybrid techniques of image coding over the past years is also reviewed. An attempt is made to highlight the neuro-wavelet approach for enhancing coding efficiency.  ...  on image compression, section V is devoted to hybrid techniques to image compression followed by VQbased hybrid techniques in section V.1, wavelet-based hybrid techniques in section V.2, ANN-based hybrid  ... 
arXiv:1209.5695v1 fatcat:z2ozolh33nh4fifyurt2quwbya

MGARD+: Optimizing Multilevel Methods for Error-bounded Scientific Data Reduction [article]

Xin Liang, Ben Whitney, Jieyang Chen, Lipeng Wan, Qing Liu, Dingwen Tao, James Kress, Dave Pugmire, Matthew Wolf, Norbert Podhorszki, Scott Klasky
2020 arXiv   pre-print
lossy compression.  ...  Experiments demonstrate that our optimizations improve the decomposition/recomposition performance of the existing multilevel method by up to 70X, and the proposed compression method can improve compression  ...  The hybrid model proposed in [9] significantly improves the compression quality by integrating ZFP's orthogonal transform in the SZ compression framework.  ... 
arXiv:2010.05872v2 fatcat:6i776iolfbdybc62xapamlpiy4

Progressive 3-D Coding of Hyperspectral Images Based on JPEG 2000

B. Penna, T. Tillo, E. Magli, G. Olmo
2006 IEEE Geoscience and Remote Sensing Letters  
Both onboard and on-the-ground compression are addressed.  ...  Index Terms-Three-dimensional set partitioning in hierarchical trees (3D-SPIHT), discrete wavelet transform (DWT), hyperspectral data, JPEG 2000, lossless and lossy compression, wavelet.  ...  Lossless compression is typically carried out by means of prediction-based approaches such as those in [1] - [5] .  ... 
doi:10.1109/lgrs.2005.859942 fatcat:b552xr4xhfgzlb6jayjlt4udau

Healthcare Cloud Integration using Distributed Cloud Storage and Hybrid Image Compression

Sherif E.Hussein, Sherif M. Badr
2013 International Journal of Computer Applications  
In this research, distributed cloud storage that can interact with many cloud providers was used as a backend while hybrid image compression/decompression technique was used in the front end.  ...  Cloud computing on the other hand; provides elastic services, high performance and scalable data storage to a large and everyday increasing number of healthcare users.  ...  This work showed the quality of JPEG and wavelet-based compression. Chen and Tseng [11] proposed a wavelet-based compression scheme with an adaptive prediction for medical images.  ... 
doi:10.5120/13839-1268 fatcat:4tud3s3fbredlckms6aiiyalqi

Multispectral Image Coding [chapter]

Tretter Daniel, Memon Nasir, Charles A. Bouman
2005 Handbook of Image and Video Processing  
There are essentially two main approaches used for lossless image compression. The first is the traditional DPCM approach based on prediction followed by context modeling of prediction errors.  ...  Reversible transform based techniques An alternative approach to lossless image compression, that has emerged recently is based on subband decomposition.  ... 
doi:10.1016/b978-012119792-6/50107-8 fatcat:ock34euztja5dkf7u6h3scmbby

Exploration of Pattern-Matching Techniques for Lossy Compression on Cosmology Simulation Data Sets [article]

Dingewn Tao, Sheng Di, Zizhong Chen, Franck Cappello
2017 arXiv   pre-print
In this work, we propose a pattern-matching (similarity searching) technique to optimize the prediction accuracy and compression ratio of SZ lossy compressor on the HACC data sets.  ...  Experiments show that our proposed optimization approach can improve the prediction accuracy and reduce the compressed size of quantization codes compared with SZ.  ...  , and perform publicly and display publicly, by or on behalf of the Government.  ... 
arXiv:1707.08205v2 fatcat:g2yxhdzlufhw5ohglsd6rfehce

Significantly Improving Lossy Compression for Scientific Data Sets Based on Multidimensional Prediction and Error-Controlled Quantization

Dingwen Tao, Sheng Di, Zizhong Chen, Franck Cappello
2017 2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS)  
Our key contribution is significantly improving the prediction hitting rate (or prediction accuracy) for each data point based on its nearby data values along multiple dimensions.  ...  One serious challenge is that the data prediction has to be performed based on the preceding decompressed values during the compression in order to guarantee the error bounds, which may degrade the prediction  ...  • We design an adaptive error-controlled quantization and variable-length encoding model in order to optimize the compression quality.  ... 
doi:10.1109/ipdps.2017.115 dblp:conf/ipps/TaoDCC17 fatcat:ocwicvakpbeszeqgaduiilj6du

Trends and Perspectives in Image and Video Coding

T. Sikora
2005 Proceedings of the IEEE  
The objective of the paper is to provide an overview on recent trends and future perspectives in image and video coding.  ...  Novel techniques targeted at achieving higher compression gains, error robustness, and network/device adaptability are described and discussed.  ...  An analysis reveals that all these video compression standards are designed around the successful block-based hybrid MC/DCT algorithm.  ... 
doi:10.1109/jproc.2004.839601 fatcat:5pxtyhojgzcafkbiqpq7dlpsla

Image Compression Based on Deep Learning: A Review

Hajar Maseeh Yasin, Adnan Mohsin Abdulazeez
2021 Asian Journal of Research in Computer Science  
Image compression is an essential technology for encoding and improving various forms of images in the digital era.  ...  , classify, and compress images.  ...  Lossy Compression It is focused primarily on file size after compression, where the size of the image is significantly reduced, but the image quality will diminish relative to the original image.  ... 
doi:10.9734/ajrcos/2021/v8i130193 fatcat:2fe4mfuvbffwphwtnxmay74oem

Learning End-to-End Lossy Image Compression: A Benchmark [article]

Yueyu Hu, Wenhan Yang, Zhan Ma, Jiaying Liu
2021 arXiv   pre-print
The literature is organized based on several aspects to jointly optimize the rate-distortion performance with a neural network, i.e., network architecture, entropy model and rate control.  ...  By introducing a coarse-to-fine hyperprior model for entropy estimation and signal reconstruction, we achieve improved rate-distortion performance, especially on high-resolution images.  ...  Further cross-metric evaluation indicates the future research direction of jointly optimizing an image compression method for both machine intelligence systems and human perception.  ... 
arXiv:2002.03711v4 fatcat:47d2ybnvmbhvtjp3lxqkkvxjq4
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