Results 151 to 160 of about 3,598 (204)

Lossless compression of already compressed textures

Proceedings of the ACM SIGGRAPH Symposium on High Performance Graphics, 2011
Texture compression helps rendering by reducing the footprint in graphics memory, thus allowing for more textures, and by lowering the number of memory accesses between the graphics processor and memory, increasing performance and lowering power consumption.
Jacob Ström, Per Wennersten
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A Lossless-by-Lossy Approach to Lossless Image Compression

2006 International Conference on Image Processing, 2006
This paper proposes a method of lossless image coding by the aid of lossy image coding. It aims at an improvement in the compression efficiency. We apply a kind of embedded coding to large coefficients in magnitude in a wavelet transform domain. The other wavelet coefficients are encoded by a context-based entropy coding.
Kazuma Shinoda, Hisakazu Kikuchi, Shogo Muramatsu   +2 more
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Lossless compression of seismic data

Journal of the Franklin Institute, 2006
Data compression techniques are commonly used to achieve a low bit rate in the digital representation of signals for efficient processing, transmission, and storage. In this paper, a new technique for lossless compression of seismic data is introduced. The technique consists of two stages.
Abdulaziz O. Abanmi, Saleh A. Alshebeili, Tariq Alamri   +2 more
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Lossless compression of Peanoscanned images

Journal of Electronic Imaging, 1994
Peanoscanning was used to obtain the pixels from an image by following a scan path described by a space-filling curve, the Peano-Hilbert curve. The Peanoscanned data were then compressed without loss of information by direct Huffrnan, arithmetic, and Lernpel-Ziv-Welch coding, as well as predictive and transform coding.
Joseph A. Provine, Rangaraj M. Rangayyan
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Lossless Compression of Random Forests

Journal of Computer Science and Technology, 2019
Ensemble methods are among the state-of-the-art predictive modeling approaches. Applied to modern big data, these methods often require a large number of sub-learners, where the complexity of each learner typically grows with the size of the dataset. This phenomenon results in an increasing demand for storage space, which may be very costly.
Amichai Painsky, Saharon Rosset
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Lossless compression of video sequences

IEEE Transactions on Communications, 1996
We investigate lossless compression schemes for video sequences. A simple adaptive prediction scheme is presented that exploits temporal correlations or spectral correlations in addition to spatial correlations. It is seen that even with motion compensation, schemes that utilize only temporal correlations do not perform significantly better than ...
Nasir D. Memon, Khalid Sayood
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Lossless compression of AVIRIS images

IEEE Transactions on Image Processing, 1996
Adaptive DPCM methods using linear prediction are described for the lossless compression of hyperspectral (224-band) images recorded by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The methods have two stages-predictive decorrelation (which produces residuals) and residual encoding.
R. E. Roger, Michael C. Cavenor
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Multiresolution lossless compression scheme

Proceedings of 3rd IEEE International Conference on Image Processing, 2002
A multiresolution lossless image compression scheme based on several new tools will be presented in this paper. An improved multiresolution Haar transform will be developed, combined with pre- and post-processing and with a new entropy coder, to give the overall compression scheme.
Patrick Piscaglia, Benoît Macq
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Lossless Compression of Hyperspectral Imagery

2011 First International Conference on Data Compression, Communications and Processing, 2011
In this paper we review the Spectral oriented Least SQuares (SLSQ) algorithm : an efficient and low complexity algorithm for Hyper spectral Image loss less compression, presented in [2]. Subsequently, we consider two important measures : Pearson's Correlation and Bhattacharyya distance and describe a band ordering approach based on this distances ...
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Lossless compression of seismic data

SEG Technical Program Expanded Abstracts 1996, 1996
A lossless method for seismic data compression has been developed. The method uses the idea of converting a signal data compression problem into a text compression problem. The conversion is based on data slicing, a reformatting process where the binary representation of a data set is rearranged, effectively separating compressible from uncompressible ...
Jeričević, Željko, Sitton, Gary A.
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