Publication

An improved decoding scheme for Matching Pursuit Streams

Pierre Vandergheynst
2005
Reports

Abstract

This work presents an improved coefficient decoding method for Matching Pursuit streams. It builds on the adaptive a posteriori quantization of coefficients, and implements an interpolation scheme that enhances the inverse quantization performance at the decoder. A class of interpolation functions is introduced, that capture the behavior of coefficients after conditional scalar quantization. The accuracy of the interpolation scheme is verified experimentally, and the novel decoding algorithm is further evaluated in image coding applications. It can be seen that the proposed method improves the rate-distortion performance by up to 0.5 dB, only by changing the reconstruction strategy at the decoder.

Official source

https://infoscience.epfl.ch/entities/publication/1de8717f-13ce-405b-aaf6-1e18a3653ab6

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Pierre Vandergheynst
2005
Reports

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/1de8717f-13ce-405b-aaf6-1e18a3653ab6

About this result

Related concepts (26)

Quantization (signal processing)

Quantization, in mathematics and digital signal processing, is the process of mapping input values from a large set (often a continuous set) to output values in a (countable) smaller set, often with a finite number of elements. Rounding and truncation are typical examples of quantization processes. Quantization is involved to some degree in nearly all digital signal processing, as the process of representing a signal in digital form ordinarily involves rounding. Quantization also forms the core of essentially all lossy compression algorithms.

Multivariate interpolation

In numerical analysis, multivariate interpolation is interpolation on functions of more than one variable (multivariate functions); when the variates are spatial coordinates, it is also known as spatial interpolation. The function to be interpolated is known at given points and the interpolation problem consists of yielding values at arbitrary points . Multivariate interpolation is particularly important in geostatistics, where it is used to create a digital elevation model from a set of points on the Earth's surface (for example, spot heights in a topographic survey or depths in a hydrographic survey).

Rate–distortion theory

Rate–distortion theory is a major branch of information theory which provides the theoretical foundations for lossy data compression; it addresses the problem of determining the minimal number of bits per symbol, as measured by the rate R, that should be communicated over a channel, so that the source (input signal) can be approximately reconstructed at the receiver (output signal) without exceeding an expected distortion D. Rate–distortion theory gives an analytical expression for how much compression can be achieved using lossy compression methods.

Related publications (27)

An improved decoding scheme for Matching Pursuit Streams

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