Marco Bressan, Gabriela Csurka, Sebastien Favre



Image enhancement is mostly driven by intent and its future largely relies on our ability to map the space of intentions with the space of possible enhancements. Taking into account the semantic content of an image is an important step in this direction where contextual and aesthetic dimensions are also likely to have an important role. In this article we detail the state-of-the-art and some recent efforts in for semantic or content-dependent enhancement. Through a concrete example we also show how image understanding and image enhancement tools can be brought together. We show how the mapping between semantic space and enhancements can be learnt from user evaluations when the purpose is subjective quality measured by user preference. This is done by introducing a discretization of both spaces and notions of coherence, agreement and relevance to the user response. Another example illustrates the feasibility of solving the situation where the binary option of whether or not to enhance is considered.


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Paper Citation

in Harvard Style

Bressan M., Csurka G. and Favre S. (2007). TOWARDS INTENT DEPENDENT IMAGE ENHANCEMENT - State-of-the-art and Recent Attempts . In Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, ISBN 978-972-8865-74-0, pages 208-218. DOI: 10.5220/0002068202080218

in Bibtex Style

author={Marco Bressan and Gabriela Csurka and Sebastien Favre},
title={TOWARDS INTENT DEPENDENT IMAGE ENHANCEMENT - State-of-the-art and Recent Attempts},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,},

in EndNote Style

JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,
TI - TOWARDS INTENT DEPENDENT IMAGE ENHANCEMENT - State-of-the-art and Recent Attempts
SN - 978-972-8865-74-0
AU - Bressan M.
AU - Csurka G.
AU - Favre S.
PY - 2007
SP - 208
EP - 218
DO - 10.5220/0002068202080218