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Set theoretic compression with an application to image coding

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Omnidirectional images are the spherical visual signals that provide a wide, 360◦, view of a scene from a specific position. Such images are becoming increasingly popular in fields like virtual reality and robotics. Compared to conventional 2D images, the ...

2020

Image Compression and Quality Assessment using Convolutional Neural Networks

Pinar Akyazi

The rapid development of digital imaging and video has placed visual contents in the heart of our lives. Digital multimedia span a vast number of areas from business to leisure, including but not limited to education, medicine, accessibility, training, adv ...

EPFL2020

Comprehensive assessment of image compression algorithms

Touradj Ebrahimi, Evgeniy Upenik, Michela Testolina

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 ...

2020

Joint Segmentation and Path Classification of Curvilinear Structures

Pascal Fua, Agata Justyna Mosinska, Mateusz Kozinski

Detection of curvilinear structures in images has long been of interest. One of the most challenging aspects of this problem is inferring the graph representation of the curvilinear network. Most existing delineation approaches first perform binary segment ...

2020

Identification of blowing snow particles in images from a Multi-Angle Snowflake Camera

Alexis Berne, Christophe Praz, Mathieu Oscar Schaer

A new method to automatically discriminate between hydrometeors and blowing snow particles on MultiAngle Snowflake Camera (MASC) images is introduced. The method uses four selected descriptors related to the image frequency, the number of particles detecte ...

COPERNICUS GESELLSCHAFT MBH2020

Graph-based image representation learning

Renata Khasanova

Though deep learning (DL) algorithms are very powerful for image processing tasks, they generally require a lot of data to reach their full potential. Furthermore, there is no straightforward way to impose various properties, given by the prior knowledge a ...

EPFL2019

Neural BTF Compression and Interpolation

Wenzel Alban Jakob

The Bidirectional Texture Function (BTF) is a data-driven solution to render materials with complex appearance. A typical capture contains tens of thousands of images of a material sample under varying viewing and lighting conditions. While capable of fait ...

WILEY2019

Perceptual Quality Study On Deep Learning Based Image Compression

Touradj Ebrahimi, Pinar Akyazi

Recently deep learning based image compression has made rapid advances with promising results based on objective quality metrics. However, a rigorous subjective quality evaluation on such compression schemes have rarely been reported. This paper aims at pe ...

IEEE2019

In this paper, two new end-to-end image compression architectures based on convolutional neural networks are presented. The proposed networks employ 2D wavelet decomposition as a preprocessing step before training and extract features for compression from ...

2019

Joint Segmentation and Path Classification of Curvilinear Structures

Pascal Fua, Agata Justyna Mosinska, Mateusz Kozinski

2019