Explore the words cloud of the INCOVID project. It provides you a very rough idea of what is the project "INCOVID" about.
The following table provides information about the project.
UNIVERSITAT DES SAARLANDES
|Coordinator Country||Germany [DE]|
|Total cost||2˙460˙000 €|
|EC max contribution||2˙460˙000 € (100%)|
1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
|Duration (year-month-day)||from 2017-10-01 to 2022-09-30|
Take a look of project's partnership.
|1||UNIVERSITAT DES SAARLANDES||DE (SAARBRUCKEN)||coordinator||2˙460˙000.00|
Generating huge amounts of visual data, be it images or videos, has never been easier than today. This creates a growing demand for lossy codecs (coders and decoders) that produce visually convincing results also for very high compression rates. Popular transform-based codecs such as JPEG and JPEG 2000 have reached a state where one cannot expect significant improvements anymore. To go beyond their limitations, fundamentally different ideas are needed.
Inpainting-based codecs can change this situation. They store only a small, carefully optimised part of the data. In the decoding step, the missing information is filled in with a suitable inpainting mechanism. A successful realisation of inpainting-based codecs can offer decisive advantages over transform-based codecs: The stored information is more intuitive and closer to the mechanisms of human perception. Moreover, the concept is very flexible: It allows to integrate a number of different features and can be tailored towards dedicated applications. Most importantly, the higher the compression rate, the larger are the qualitative advantages over transform-based codecs.
However, the potential of these codecs is widely unexplored so far, since difficult fundamental problems must be solved first. This includes optimisation of the data and the inpainting process, sophisticated data coding, and the design of real-time capable sequential and parallel numerical algorithms. We are committed to addressing all these challenges in an integrated approach: We cover the entire spectrum from its theoretical foundations over benchmarking and highly efficient numerical algorithms to codecs for specific applications, and a real-time 4K video player as demonstrator.
This will lift inpainting methods from a visually pleasant image editing tool to a fundamental paradigm in coding. Research results that enter forthcoming coding standards will also have an impact on everybody's daily life.
|year||authors and title||journal||last update|
Leif Bergerhoff, Marcello Cardenas, Joachim Weickert, Martin Welk
Modelling Stable Backward Diffusion and Repulsive Swarms with Convex Energies and Range Constraints
published pages: 409-423, ISSN: , DOI:
|Lecture Notes in Computer Science Vol. 10746||2019-08-05|
Martin Fuchs, Jan MÃ¼ller, Christian Tietz, Joachim Weickert
Convex Regularization of Multi-Channel Images Based on Variants of the TV-Model
published pages: 976-995, ISSN: 1747-6933, DOI:
|Complex Variables and Elliptic Equations Vol. 63, No. 7-8||2019-08-05|
Bergerhoff, Leif; Weickert, Joachim; Dar, Yehuda
Algorithms for Piecewise Constant Signal Approximations
published pages: , ISSN: , DOI:
|arXiv Preprint, submitted to the EUSIPCO 2019 conference 1||2019-08-05|
J. A. TÃ³masson, P. Ochs, J. Weickert
AFSI: Adaptive restart for fast semi-iterative schemes for convex optimisation
published pages: 669-681, ISSN: , DOI:
|Lecture Notes in Computer Science Vol. 11269||2019-08-05|
Martin Welk, Joachim Weicker, Guy Gilboa
A Discrete Theory and Efficient Algorithms for Forward-and-Backward Diffusion Filtering
published pages: 13991426, ISSN: 1573-7683, DOI:
|Journal of Mathematical Imaging and Vision Vol. 60, No. 9||2019-08-05|
Lena Karos, Pinak Bheed, Pascal Peter, and Joachim Weickert
Optimising Data for Exemplar-based Inpainting
published pages: 547â€“558, ISSN: , DOI:
|Lecture Notes in Computer Science Vol. 11182||2019-08-05|
Bergerhoff, Leif; CÃ¡rdenas, Marcelo; Weickert, Joachim; Welk, Martin
Stable Backward Diffusion Models that Minimise Convex Energies
published pages: , ISSN: , DOI:
|arXiv, to be submitted to Journal of Mathematical Imaging and Vision 1||2019-08-05|
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