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Data-Driven Parameter Choice for Illumination Artifact Correction of Digital Images

Abstract : We propose a new procedure for image illumination correction with data-driven parameter choice. This procedure aims at estimating the reflectance image from a corrupted version in which the corruption is due to pointwise multiplicative illumination artifact. The log-illumination artefact consists of "smooth" variations of the intensity which are modelled by a function lying in a finite dimensional space. Then a γ-correction is incorporated. The question of model selection is difficult to solve. We propose an entropy minimization criterion for the selection of both the approximating log-illumination space dimension and the γ-coefficient, so that no parameter tuning is needed. Several experiments are presented using this approach. A comparison to other methods illustrates the relevance of this approach.
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Contributor : Ségolen Geffray Connect in order to contact the contributor
Submitted on : Monday, January 10, 2022 - 2:11:54 PM
Last modification on : Friday, January 14, 2022 - 3:11:33 AM


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  • HAL Id : hal-03519325, version 1



Hong-Phuong Dang, Myriam Vimond, Ségolen Geffray. Data-Driven Parameter Choice for Illumination Artifact Correction of Digital Images. IEEE Signal Processing Letters, Institute of Electrical and Electronics Engineers, 2021. ⟨hal-03519325⟩



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