Results 231 to 240 of about 99,410 (264)

Lossless, near-lossless, and refinement coding of bilevel images

IEEE Transactions on Image Processing, 1999
We present general and unified algorithms for lossy/lossless coding of bilevel images. The compression is realized by applying arithmetic coding to conditional probabilities. As in the current JBIG standard the conditioning may be specified by a template. For better compression, the more general free tree may be used.
B, Martins, S, Forchhammer
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A progressive Lossless/Near-Lossless image compression algorithm

IEEE Signal Processing Letters, 2002
A novel image compression technique is presented that incorporates progressive transmission and near-lossless compression in a single framework. Experimental performance of the proposed coder proves to be competitive with the state-of-the-art compression schemes.
I. Avcibas, N. Memon, B. Sankur, K. Sayood   +3 more
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Lossless ECG encoding

Computer Methods and Programs in Biomedicine, 1997
We have studied the lossless encoding of ECG signals. With suitable code we aim to reduce the storage space needed by ECG signals. Several methods designed for ECG compression use lossy, i.e. irreversible techniques, in which the original signal is lost, but the restored approximation is almost equal to the original.
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Context Adaptive Lossless and Near-Lossless Coding for Digital Angiographies

2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007
This paper presents a context adaptive coding method for image sequences in hemodynamics. The proposed method implements motion compensation through of a two-stage context adaptive linear predictor. It is robust to the local intensity changes and the noise that often degrades these image sequences, and provides lossless and near-lossless quality.
Rafael A P, dos Santos, Jacob, Scharcanski   +1 more
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Lossless integer wavelet transform

IEEE Signal Processing Letters, 1997
Signal compression can be obtained by wavelet transformation of integer input data followed by quantification and coding. As the quantification is usually lossy, the whole compression/decompression scheme is lossy too. We define a critical wavelet coefficient quantification, i.e., the coarsest quantification that allows perfect reconstruction.
Dewitte, Steven, Jan, Cornelis
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Lossless and near-lossless compression of EEG signals

Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136), 2002
In this paper we study compression techniques for electroencephalograph (EEG) signals. A variety of lossless compression techniques, ranging from simple dictionary based approaches to more sophisticated context modeling techniques based on work in lossless image coding are investigated and compared.
J. Cinkler, X. Kong, N. Memon
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Semi-lossless text compression

Data Compression Conference, 2004. Proceedings. DCC 2004, 2004
A new notion, that of semi-lossless text compression, is introduced, and its applicability in various settings is investigated. First results suggest that it might be hard to exploit the additional redundancy of English texts, but the new methods could be useful in applications where the correct spelling is not important, such as in short emails, and ...
Kaufman, Yair, Klein, Shmuel T.
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Context-based lossless and near-lossless compression of EEG signals

IEEE Transactions on Information Technology in Biomedicine, 1999
In this paper, we study compression techniques for electroencephalograph (EEG) signals. A variety of lossless compression techniques, including compress, gzip, bzip, shorten, and several predictive coding methods, are investigated and compared. The methods range from simple dictionary-based approaches to more sophisticated context modeling techniques ...
N, Memon, X, Kong, J, Cinkler
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Interconnection of -lossless behaviours

Systems & Control Letters, 2010
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Lossless and near-lossless compression of still color images

Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348), 2003
This paper proposes a unified coding algorithm for lossless and near-lossless color image compression that exploits the correlations between RGB signals. For lossless coding, a reversible color transform is proposed that removes the correlations between RGB signals while avoiding any finite word length limitation.
T. Nakachi, T. Fujii, J. Suzuki
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