Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Concept

Lempel-Ziv-Welch

Publications associées (16)

High-Throughput Lossy-to-Lossless 3D Image Compression

Gilles Fourestey, Félix Schmidt

The rapid increase in medical and biomedical image acquisition rates has opened up new avenues for image analysis, but has also introduced formidable challenges. This is evident, for example, in selective plane illumination microscopy where acquisition rat ...

Institute of Electrical and Electronics Engineers2021

Fast Block Sequential Decoding of Polar Codes

Kirill Ivanov

A reduced complexity sequential decoding algorithm for polar (sub) codes is described. The proposed approach relies on a decomposition of the polar (sub) code being decoded into a number of outer codes, and on-demand construction of codewords of these code ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Comprehensive assessment of image compression algorithms

Touradj Ebrahimi, Michela Testolina, Evgeniy Upenik

JPEG image coding standard has been a dominant format in a wide range of applications in soon three decades since it has been released as an international standard. The landscape of applications and services based on pictures has evolved since the original ...

SPIE2020

A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free!

Martin Jaggi, Anastasiia Koloskova

Decentralized optimization methods enable on-device training of machine learning models without a central coordinator. In many scenarios communication between devices is energy demanding and time consuming and forms the bottleneck of the entire system. We ...

MICROTOME PUBLISHING2020

Dictionary Compression in Point Cloud Data Management

Anastasia Ailamaki, Mirjana Pavlovic

Nowadays, massive amounts of point cloud data can be collected thanks to advances in data acquisition and processing technologies such as dense image matching and airborne LiDAR scanning. With the increase in volume and precision, point cloud data offers a ...

ASSOC COMPUTING MACHINERY2019

PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization

Martin Jaggi, Thijs Vogels

We study lossy gradient compression methods to alleviate the communication bottleneck in data-parallel distributed optimization. Despite the significant attention received, current compression schemes either do not scale well, or fail to achieve the target ...

2019

A graph learning approach for light field image compression

Pascal Frossard, Touradj Ebrahimi, Hermina Petric Maretic, Irene Viola

In recent years, light field imaging has attracted the attention of the academic and industrial communities thanks to its enhanced rendering capabilities that allow to visualise contents in a more immersive and interactive way. However, those enhanced capa ...

Spie-Int Soc Optical Engineering2018

Airborne Hyperspectral Imaging of Lakes

Kevin Sylvain Barbieux

In a time of rising concern about climate change and pollution, the water quality of large lakes acts as an indicator of the health of the environment. To study the water quality at a large scale - up to several hundreds of kilometres - hyperspectral remot ...

EPFL2018

Adaptive Learning-Based Compressive Sampling for Low-power Wireless Implants

Yusuf Leblebici, Volkan Cevher, Catherine Dehollain, Mahsa Shoaran, Luca Baldassarre, Franco Maloberti, Cosimo Aprile, Kerim Türe, Gürkan Yilmaz

Implantable systems are nowadays being used to interface the human brain with external devices, in order to understand and potentially treat neurological disorders. The most predominant design constraints are the system’s area and power. In this paper, we ...

2018

Dictionary Compression in Point Cloud Data Management

Anastasia Ailamaki, Mirjana Pavlovic

Nowadays, massive amounts of point cloud data can be collected thanks to advances in data acquisition and processing technologies like dense image matching and airborne LiDAR (Light Detection and Ranging) scanning. With the increase in volume and precision ...

2017

Parameterized SVM for Personalized Drug Concentration Prediction

Giovanni De Micheli, Alena Simalatsar, Wenqi You Dubout

This paper proposes a parameterized Support Vector Machine (ParaSVM) approach for modeling the Drug Concentration to Time (DCT) curves. It combines the merits of Support Vector Machine (SVM) algorithm that considers various patient features and an analytic ...

2013

Compression of Multispectral Images: Color (RGB) plus Near-Infrared (NIR)

Sabine Süsstrunk, Zahra Sadeghipoor Kermani, Neda Salamati

We propose a compression framework for four-channel images, composed of color (RGB) and near-infrared (NIR) channels, which exploits the correlation between the visible and the NIR information. The high-frequency components of both visible and NIR scene re ...

Ieee2012

Polar Codes are Optimal for Lossy Source Coding

Rüdiger Urbanke

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

Geometry-Based Distributed Scene Representation With Omnidirectional Vision Sensors

Pascal Frossard, Ivana Tosic

This paper addresses the problem of efficient representation of scenes captured by distributed omnidirectional vision sensors. We propose a novel geometric model to describe the correlation between different views of a 3-D scene. We first approximate the c ...

2008

Space-frequency quantization for image compression with directionlets

Martin Vetterli, Vladan Velisavljevic

The standard separable 2-D wavelet transform (WT) has recently achieved a great success in image processing because it provides a sparse representation of smooth images. However, it fails to efficiently capture 1-D discontinuities, like edges or contours. ...

2007

On the Use of Masking Models for Image and Audio Watermarking

In most watermarking systems, masking models, inherited from data compression algorithms, are used to preserve fidelity by controlling the perceived distortion resulting from adding the watermark to the original signal. So far, little attention has been pa ...

2005