Dr. Evgeniy Upenik Profile

Dr. Evgeniy Upenik

Scientist

SPIE Involvement:

Author

Area of Expertise:

Image and video processing , Deep learning

Evgeniy Upenik is a researcher and an engineer. His field of interest covers a wide area ranging from image and video compression to immersive communication and virtual reality, as well as deep learning. He received his PhD degree in electrical engineering from École Polytechnique Fédérale de Lausanne. Evgeniy has been actively involved in standardization for many years where he co-chaired JPEG AI Learning-Based Image Coding System activity at ISO/IEC JTC 1/SC 29/WG 1. Previously, Evgeniy was a software engineer specializing in video compression.

Proceedings Article | 4 October 2023 Presentation + Paper

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

Michela Testolina, Evgeniy Upenik, Touradj Ebrahimi

Proceedings Volume 12674, 126740Q (2023) https://doi.org/10.1117/12.2677347

KEYWORDS: Image quality, Image compression, Image quality standards, Visual compression, Image processing, Image visualization, Standards development

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Proceedings Article | 3 October 2022 Presentation + Paper

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

Michela Testolina, Evgeniy Upenik, Jon Sneyer, Touradj Ebrahimi

Proceedings Volume 12226, 122260D (2022) https://doi.org/10.1117/12.2636687

KEYWORDS: Image quality, Image compression, Image quality standards

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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 artifacts, whose visibility depends on the chosen bitrate. Modern applications target images with high to near-visually lossless quality, in order to maximize the visual quality while still reducing storage space consumption. In this context, subjective and objective image quality assessment are essential tools in order to develop compression methods able to generate images with high visual quality. While a large variety of subjective quality assessment protocols have been standardized in the past, they have been found to be imprecise in the quality interval from high to near-visually lossless. Similarly, an objective quality metric designed to work specifically in the mentioned range has not been designed yet. As current quality assessment methodologies have proven to be unreliable, a renewed activity on the Assessment of Image Coding, also referred to as JPEG AIC, was recently launched by the JPEG Committee. The goal of this activity is to extend previous standardization efforts, i.e. AIC Part 1 and AIC Part 2 (also know as AIC-1 and AIC-2), by developing a new standard, known as AIC Part 3 (or AIC-3). Notably, the goal of the activity is to standardize both subjective and objective visual quality assessment methods, specifically targeting images with quality in the range from high to near-visually lossless. Two Draft Calls for Contributions on Subjective Image Quality Assessment1, 2 were released, aiming at collecting contributions on new methods and best practices for subjective image quality assessment in the target quality range, while a Call for Proposals on Objective Image Quality Assessment is expected to be released at a later date. This paper aims at summarizing past JPEG AIC efforts and reviewing the main objectives of the future activities, outlining the scope of the activity, the main use cases and requirements, and call for contributions. Finally, conclusions on the activity are drawn.

Proceedings Article | 1 August 2021 Presentation + Paper

Towards a secure and trustworthy imaging with non-fungible tokens

Nicolas Martinod, Kambiz Homayounfar, Davi Lazzarotto, Evgeniy Upenik, Touradj Ebrahimi

Proceedings Volume 11842, 1184218 (2021) https://doi.org/10.1117/12.2598436

KEYWORDS: Standards development, Legal, Digital imaging, Computer security

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Proceedings Article | 1 August 2021 Presentation + Paper

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

Evgeniy Upenik, Michela Testolina, Touradj Ebrahimi

Proceedings Volume 11842, 118421N (2021) https://doi.org/10.1117/12.2597833

KEYWORDS: Image compression, Super resolution, Visualization, Image quality, Image resolution, Image processing, Neural networks

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Proceedings Article | 1 August 2021 Presentation + Paper

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

Michela Testolina, Evgeniy Upenik, Touradj Ebrahimi

Proceedings Volume 11842, 118421A (2021) https://doi.org/10.1117/12.2597828

KEYWORDS: Denoising, Image compression, Visualization, Image denoising, Image processing, Visual compression, Image quality, Cameras

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Proceedings Article | 21 August 2020 Presentation + Paper

Machine learning based detection of digital documents maliciously recaptured from displays

Saleh Gholam-Zadeh, Evgeniy Upenik, Guy Hatarsi, Touradj Ebrahimi

Proceedings Volume 11510, 115100U (2020) https://doi.org/10.1117/12.2569256

KEYWORDS: Data modeling, Machine learning, Digital imaging, Image forensics

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Proceedings Article | 21 August 2020 Presentation + Paper

Comprehensive assessment of image compression algorithms

Michela Testolina, Evgeniy Upenik, Touradj Ebrahimi

Proceedings Volume 11510, 1151020 (2020) https://doi.org/10.1117/12.2569255

KEYWORDS: Image compression, Image quality, Visual compression, Transparency, Standards development

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Proceedings Article | 21 August 2020 Presentation + Paper

High dynamic range image sharing with privacy protection

Evgeniy Upenik, Pol Fernandez Marti, Touradj Ebrahimi

Proceedings Volume 11510, 1151023 (2020) https://doi.org/10.1117/12.2569112

KEYWORDS: High dynamic range imaging, Image restoration, Image processing, LCDs, Computer programming, Cameras, Reconstruction algorithms, Visualization, Image encryption

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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 well-known fact that pictures contain information that could cause various security and privacy issues. This is in particular true because high dynamic range pictures exhibit more information when compared to conventional images resulting in an increased invasion of privacy. Lack of proper solutions to overcome privacy can hinder a wide spread adoption of high dynamic range pictures shared in social networks. For example, dark areas of a content that are otherwise difficult to view in a conventional picture become more visible. It is therefore natural that mechanisms are offered to protect privacy while sharing pictures also in high dynamic range. In this paper, we propose an architecture to share high dynamic range images captured by high-end smartphones while offering a mechanism to protect privacy. In our approach, the high dynamic range picture is tone-mapped into a lower dynamic range version which reduces its degree of invasiveness as far as privacy is concerned. Eventually, any remaining privacy sensitive areas in the picture can be further protected (blurring of faces, masking cars licence plates, etc.). The core of the proposed architecture conforms to both JPEG XT, a recently standardised format that offers backward compatibility with legacy JPEG and to JPEG Systems under development. The proposed solution allows to publicly share a protected version of the high dynamic range image tone-mapped to a standard dynamic range picture. The latter can go through transmorphing operation to further protect it. Authorised users can access the original high dynamic range picture. The architecture as described above has been implemented as an app for smartphones running Android OS. We demonstrate feasibility and usefulness of this approach and discuss its advantages when compared to conventional image sharing such as those used in social networks.

Proceedings Article | 1 April 2020 Presentation + Paper

Benchmarking JPEG XL image compression

Jyrki Alakuijala, Sami Boukortt, Touradj Ebrahimi, Evgenii Kliuchnikov, Jon Sneyers, Evgeniy Upenik, Lode Vandevenne‎, Luca Versari, Jan Wassenberg

Proceedings Volume 11353, 113530X (2020) https://doi.org/10.1117/12.2556264

KEYWORDS: Image compression, Computer programming, Visualization, Image quality, Photography, Image processing, Visual compression, Internet, Multimedia signal processing, Standards development

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Proceedings Article | 28 September 2016 Presentation + Paper

JPEG backward compatible coding of omnidirectional images

Martin Řeřábek, Evgeniy Upenik, Touradj Ebrahimi

Proceedings Volume 9971, 99711O (2016) https://doi.org/10.1117/12.2240281

KEYWORDS: Image compression, Video, Visualization, Panoramic photography, Spherical lenses, Visual process modeling, Computer programming, Visual compression, Information visualization, Optical spheres

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