Publications de Evgeniy Upenik

On the assessment of high-quality images: advances on the JPEG AIC-3 activity

Touradj Ebrahimi, Evgeniy Upenik, Michela Testolina

Recent advances in image compression have made it both possible and desirable for image quality to approach the visually lossless range. However, the most commonly used subjective visual quality assessment protocols, e.g. those reported in ITU-T Rec. BT.50 ...

2023

Towards JPEG AIC part 3: visual quality assessment of high to visually lossless image coding

Touradj Ebrahimi, Evgeniy Upenik, Michela Testolina

Due to the increasing number of pictures captured and stored every day by and on digital devices, lossy image compression has become inevitable to limit the needed storage requirement. As a consequence, these compression methods might introduce some visual ...

SPIE2022

Performance Evaluation of Objective Image Quality Metrics on Conventional and Learning-Based Compression Artifacts

Touradj Ebrahimi, Evgeniy Upenik, Michela Testolina

Lossy image compression is a popular, simple and effective solution to reduce the amount of data representing digital pictures. In most lossy compression methods, the reduced volume of data in bits is achieved at the expense of introducing visual artifacts ...

2021

Towards super resolution in the compressed domain of learning-based image codecs

Touradj Ebrahimi, Evgeniy Upenik, Michela Testolina

Learning-based image coding has shown promising results during recent years. Unlike the traditional approaches to image compression, learning-based codecs exploit deep neural networks for reducing dimensionality of the input at the stage where a linear tra ...

SPIE2021

Large-Scale Crowdsourcing Subjective Quality Evaluation of Learning-Based Image Coding

Touradj Ebrahimi, Evgeniy Upenik, Michela Testolina

Learning-based image codecs produce different compression artifacts, when compared to the blocking and blurring degradation introduced by conventional image codecs, such as JPEG, JPEG~2000 and HEIC. In this paper, a crowdsourcing based subjective quality e ...

IEEE2021

Towards image denoising in the latent space of learning-based compression

Touradj Ebrahimi, Evgeniy Upenik, Michela Testolina

In recent years, learning-based image compression has demonstrated similar or superior performance when com- pared to conventional approaches in terms of compression efficiency and visual quality. Typically, learning-based image compression takes advantage ...

SPIE2021

Towards a secure and trustworthy imaging with non-fungible tokens

Touradj Ebrahimi, Evgeniy Upenik, Davi Nachtigall Lazzarotto

Non fungible tokens (NFTs) are used to define the ownership of digital assets. More recently, there has been a surge of platforms to auction digital art as well as other digital assets in form of image, video, and audio content of all sorts. Although NFTs ...

2021

Open-Set Person Re-Identification through Error Resilient Recurring Gallery Building

Touradj Ebrahimi, Evgeniy Upenik

In person re-identification, individuals must be correctly identified in images that come from different cameras or are captured at different points in time. In the open-set case, the above needs be achieved for people who have not been previously recognis ...

IEEE2021

High dynamic range image sharing with privacy protection

Touradj Ebrahimi, Evgeniy Upenik, Pol Fernandez Marti

Sharing pictures has become a very popular practice among consumers. Most recent cameras, displays, and smartphones can capture and display images in high dynamic range and wide colour gamut, contributing to an increase of this type of content. It is a wel ...

SPIE2020

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Evgeniy Upenik

On the assessment of high-quality images: advances on the JPEG AIC-3 activity

Towards JPEG AIC part 3: visual quality assessment of high to visually lossless image coding

Performance Evaluation of Objective Image Quality Metrics on Conventional and Learning-Based Compression Artifacts

Towards super resolution in the compressed domain of learning-based image codecs

Large-Scale Crowdsourcing Subjective Quality Evaluation of Learning-Based Image Coding

Towards image denoising in the latent space of learning-based compression

Towards a secure and trustworthy imaging with non-fungible tokens

Open-Set Person Re-Identification through Error Resilient Recurring Gallery Building

High dynamic range image sharing with privacy protection

Visual Attention and Perceptual Quality in Omnidirectional Imaging

Graph Chatbot

Chattez avec Graph Search

On the assessment of high-quality images: advances on the JPEG AIC-3 activity

Towards a secure and trustworthy imaging with non-fungible tokens

Visual Attention and Perceptual Quality in Omnidirectional Imaging

High dynamic range image sharing with privacy protection

Towards JPEG AIC part 3: visual quality assessment of high to visually lossless image coding

Towards super resolution in the compressed domain of learning-based image codecs

Large-Scale Crowdsourcing Subjective Quality Evaluation of Learning-Based Image Coding

Towards image denoising in the latent space of learning-based compression

Open-Set Person Re-Identification through Error Resilient Recurring Gallery Building

Performance Evaluation of Objective Image Quality Metrics on Conventional and Learning-Based Compression Artifacts