Publications associées à Oligoquantization in low-rate lossy source coding

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Polar Codes are Optimal for Lossy Source Coding

Rüdiger Urbanke, Satish Babu Korada

We consider lossy source compression of a binary symmetric source using polar codes and the low-complexity successive encoding algorithm. It was recently shown by Arikan that polar codes achieve the capacity of arbitrary symmetric binary-input discrete mem ...

Institute of Electrical and Electronics Engineers2010

Sparse Image Representation by Directionlets

Martin Vetterli, Vladan Velisavljevic, Pier Luigi Dragotti

Despite the success of the standard wavelet transform (WT) in image processing in recent years, the efficiency and sparsity of its representation are limited by the spatial symmetry and separability of its basis functions built in the horizontal and vertic ...

Elsevier2010

On the Information Rates of the Plenoptic Function

Martin Vetterli, Minh Do

The plenoptic function describes the visual information available to an observer at any point in space and time. Samples of the plenoptic function (POF) are seen in video and in general visual content (images, mosaics, panoramic scenes, etc.), and rep- res ...

Institute of Electrical and Electronics Engineers2010

Lossless Source Coding with Polar Codes

Satish Babu Korada, Harm Cronie

In this paper lossless compression with polar codes is considered. A polar encoding algorithm is developed and a method to design the code and compute the average compression rate for finite lengths is given. It is shown that the scheme achieves the optima ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

Netscope: Practical Network Loss Tomography

Patrick Thiran, Xuan Hung Nguyen, Maciej Kurant, Denisa Gabriela Ghita

We present Netscope, a tomographic technique that infers the loss rates of network links from unicast end-to-end measurements. Netscope uses a novel combination of first- and second-order moments of end-to-end measurements to identify and characterize the ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

MDCT for Encoding Residual Signals in Frequency Domain Linear Prediction

Petr Motlicek, Hynek Hermansky, Sriram Ganapathy

Frequency domain linear prediction (FDLP) uses autoregressive models to represent Hilbert envelopes of relatively long segments of speech/audio signals. Although the basic FDLP audio codec achieves good quality of the reconstructed signal at high bit-rates ...

Audio Engineering Society, 60 East 42nd Street, New York, New York 10165-2520, USA;2009

MDCT for Encoding Residual Signals in Frequency Domain Linear Prediction

Petr Motlicek, Hynek Hermansky, Sriram Ganapathy

Idiap2009

Polar Codes are Optimal for Lossy Source Coding

Rüdiger Urbanke, Satish Babu Korada

We consider lossy source compression of a binary symmetric source with Hamming distortion function. We show that polar codes combined with a low-complexity successive cancellation encoding algorithm achieve the rate-distortion bound. The complexity of both ...

2009

Oligoquantization in low-rate lossy source coding

Graph Chatbot

Chattez avec Graph Search

Polar Codes are Optimal for Lossy Source Coding

Sparse Image Representation by Directionlets

On the Information Rates of the Plenoptic Function

Lossless Source Coding with Polar Codes

Netscope: Practical Network Loss Tomography

MDCT for Encoding Residual Signals in Frequency Domain Linear Prediction

MDCT for Encoding Residual Signals in Frequency Domain Linear Prediction

Multi-experts scheduling system for real-time applications

Low bit-rate compression of omnidirectional images

Polar Codes are Optimal for Lossy Source Coding

MDCT for Encoding Residual Signals in Frequency Domain Linear Prediction

Multi-experts scheduling system for real-time applications

Low bit-rate compression of omnidirectional images

Polar Codes are Optimal for Lossy Source Coding

Lossless Source Coding with Polar Codes

On the Information Rates of the Plenoptic Function

MDCT for Encoding Residual Signals in Frequency Domain Linear Prediction

Polar Codes are Optimal for Lossy Source Coding

Netscope: Practical Network Loss Tomography

Sparse Image Representation by Directionlets