Results 271 to 280 of about 931,486 (319)
Some of the next articles are maybe not open access.
Improving Lossy Compression for SZ by Exploring the Best-Fit Lossless Compression Techniques
2021 IEEE International Conference on Big Data (Big Data), 2021In the past decades, various lossy compressors have been studied broadly due to the ever-increasing volume of data being produced by today’s scientific applications.
Jinyang Liu +7 more
semanticscholar +1 more source
Future generations computer systems
The Joint Laboratory on Extreme-Scale Computing (JLESC) was initiated at the same time lossy compression for scientific data became an important topic for the scientific communities.
Franck Cappello +19 more
semanticscholar +1 more source
The Joint Laboratory on Extreme-Scale Computing (JLESC) was initiated at the same time lossy compression for scientific data became an important topic for the scientific communities.
Franck Cappello +19 more
semanticscholar +1 more source
CUSZP2: A GPU Lossy Compressor with Extreme Throughput and Optimized Compression Ratio
International Conference for High Performance Computing, Networking, Storage and AnalysisExisting GPU lossy compressors suffer from expensive data movement overheads, inefficient memory access patterns, and high synchronization latency, resulting in limited throughput.
Yafan Huang +3 more
semanticscholar +1 more source
Lossy Image Compression with Foundation Diffusion Models
European Conference on Computer VisionIncorporating diffusion models in the image compression domain has the potential to produce realistic and detailed reconstructions, especially at extremely low bitrates.
Lucas Relic +3 more
semanticscholar +1 more source
Lossy Audio Compression via Compressed Sensing
2010 Data Compression Conference, 2010We propose a Compressed Sensing application to audio signals and analyze its audio perceptual quality with PEAQ.
Rubem J. V. de Medeiros +2 more
openaire +1 more source
2014
In this chapter we examine compression algorithms such that recovered input data cannot be exactly reconstructed from compressed version. This termed “loss”. What we have, then, is a tradeoff between efficient compression versus a less accurate version of the input data. This tradeoff is captured in the Rate-Distortion Theory.
Ze-Nian Li, Mark S. Drew, Jiangchuan Liu
openaire +1 more source
In this chapter we examine compression algorithms such that recovered input data cannot be exactly reconstructed from compressed version. This termed “loss”. What we have, then, is a tradeoff between efficient compression versus a less accurate version of the input data. This tradeoff is captured in the Rate-Distortion Theory.
Ze-Nian Li, Mark S. Drew, Jiangchuan Liu
openaire +1 more source
Lossy Audio Compression Identification
2018 26th European Signal Processing Conference (EUSIPCO), 2018We propose a system which can estimate from an audio recording that has previously undergone lossy compression the parameters used for the encoding, and therefore identify the corresponding lossy coding format. The system analyzes the audio signal and searches for the compression parameters and framing conditions which match those used for the encoding.
Bongjun Kim, Zafar Rafii
openaire +1 more source
Pointwise redundancy in lossy data compression and universal lossy data compression
IEEE Transactions on Information Theory, 2000Summary: The author characterizes achievable pointwise redundancy rates for lossy data compression at a fixed distortion level. Pointwise redundancy refers to the difference between the description length achieved by an \(n\)th-order block code and the optimal \(nR(D)\) bits.
openaire +1 more source
Restoration of lossy compressed noisy images
1996 IEEE International Symposium on Circuits and Systems. Circuits and Systems Connecting the World. ISCAS 96, 1999Noise degrades the performance of any image compression algorithm. However, at very low bit rates, image coders effectively filter noise that may he present in the image, thus, enabling the coder to operate closer to the noise free case. Unfortunately, at these low bit rates the quality of the compressed image is reduced and very distinctive coding ...
O K, Al-Shaykh, R M, Mersereau
openaire +2 more sources
Lossy Compression Tolerant Steganography
2001This paper proposes a lossy compression tolerant steganography. Steganography hides the confidential data secretly. The unauthorized people are difficult to detect hidden data. It provides a secure channel to transmit confidential information. Nowadays, it is a very important technique when we are progressively going to computer network age.
Ren-Junn Hwang +3 more
openaire +1 more source