In this work, we propose a new construction of polar lattices to achieve the rate-distortion bound memoryless Gaussian source. The structure proposed allows integrate entropy coding into lattice quantizer, which greatly simplifies compression process. overall complexity encoding and decoding is O(N log <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink...

The problem of joint universal source coding and modeling, treated in the context of lossless codes by Rissanen, was recently generalized to fixed-rate lossy coding of finitely parametrized continuous-alphabet i.i.d. sources. We extend these results to variable-rate lossy block coding of stationary ergodic sources and show that, for bounded metric distortion measures, any finitely parametrized ...

Lossy compression techniques have been applied to image and text compression, yielding compression factors that are vastly superior to lossless compression schemes. In this paper, we present a preliminary study on a set of lossy transformations for XML documents that preserve the semantics. Inspired by previous techniques, e.g. lossy text compression and literate programming, we apply a simple ...

The simulation of lossy transmission lines in time domain is a very time consuming task. It requires numerical convolutions and the solution of linear equation systems. In this paper a model for lossy transmission lines and an algorithm for the simulation of these lines is developed. Based on this an approach for parallel simulation of lossy transmission lines is presented. As this approach cov...

Data compression algorithms can be categorized into lossless and lossy. Bit streams generated by lossless compression algorithm can be faithfully recovered to the original data. If loss of one single bit may cause serious and unpredictable consequences in original data (for example, text and medical image compression) lossless compression algorithm should be applied. If data consumers can toler...

This paper outlines a scalable to lossless coder, that is the coder presented is a scalable coder that scales from lossy quality to lossless quality. Lossless compression is achieved by concatenating a lossy, scalable transform coder with a scalable scheme for the compression of the synthesis error signal. The lossless compression results obtained are comparable with the state of the art in los...

Lossy compression of hyperspectral imagery is considered with special emphasis on the preservation of anomalous pixels. In the proposed scheme, anomalous pixels are extracted before compression and replaced with interpolation from surrounding, non-anomalous pixels. The image is then coded using principal component analysis for spectral decorrelation followed by JPEG2000. The anomalous pixels do...

The submitted paper deals with the application of lossy compression to two-dimensional curves scanned grey-scale images. A new algorithm based on correlation optimization used for Space Filling Curve (SFC) determination is presented. The resulting 1-dimensional image representation provides a higher neighbour pixel similarity, similar to other methods [6]. One of such methods is the Peano-Hilbe...

We propose k-SACK, a TCP variant that has considerably improved throughput characteristics over lossy links. A k-SACK source does not consider every packet loss as an indication of congestion. It uses the Selective Acknowledgement option to estimate a parameter lookaheadloss, which is used in congestion detection. Our results demonstrate that kSACK maintains a steady performance in a non-lossy ...