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Christophe De Vleeschouwer
Researcher at Université catholique de Louvain
Publications - 152
Citations - 3677
Christophe De Vleeschouwer is an academic researcher from Université catholique de Louvain. The author has contributed to research in topics: Computer science & Pixel. The author has an hindex of 24, co-authored 134 publications receiving 2430 citations. Previous affiliations of Christophe De Vleeschouwer include École Polytechnique Fédérale de Lausanne & Catholic University of Leuven.
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Journal ArticleDOI
Color Balance and Fusion for Underwater Image Enhancement
TL;DR: This work introduces an effective technique to enhance the images captured underwater and degraded due to the medium scattering and absorption by building on the blending of two images that are directly derived from a color-compensated and white-balanced version of the original degraded image.
Proceedings ArticleDOI
O-HAZE: A Dehazing Benchmark with Real Hazy and Haze-Free Outdoor Images
TL;DR: The O-HAZE dataset as mentioned in this paper contains 45 different outdoor scenes depicting the same visual content recorded in haze-free and hazy conditions, under the same illumination parameters, using traditional image quality metrics such as PSNR, SSIM and CIEDE2000.
Proceedings ArticleDOI
D-HAZY: A dataset to evaluate quantitatively dehazing algorithms
TL;DR: A dataset that contains 1400+ pairs of images with ground truth reference images and hazy images of the same scene, built on the Middelbury and NYU Depth datasets that provide images of various scenes and their corresponding depth maps is introduced.
Journal ArticleDOI
Involvement of human ribosomal proteins in nucleolar structure and p53-dependent nucleolar stress.
Emilien Nicolas,Pascaline Parisot,Celina Pinto-Monteiro,Roxane de Walque,Christophe De Vleeschouwer,Denis L. J. Lafontaine +5 more
TL;DR: It is found that uL5 (formerly RPL11) and uL18 (RPL5) are the strongest contributors to nucleolar integrity, and together with the 5S rRNA, they form the late-assembling central protuberance on mature 60S subunits, and act as an Hdm2 trap and p53 stabilizer.
Book ChapterDOI
I-HAZE: A Dehazing Benchmark with Real Hazy and Haze-Free Indoor Images
TL;DR: A new dataset -named I-HAZE- that contains 35 image pairs of hazy and corresponding haze-free (ground-truth) indoor images that allows us to objectively compare the existing image dehazing techniques using traditional image quality metrics such as PSNR and SSIM.