Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/26440
Title: Color Balance and Fusion for Underwater Image Enhancement
Authors: ANCUTI, Codruta 
ANCUTI, Cosmin 
De Vleeschouwer, Christophe
BEKAERT, Philippe 
Issue Date: 2018
Publisher: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Source: IEEE TRANSACTIONS ON IMAGE PROCESSING, 27(1), p. 379-393
Abstract: We introduce an effective technique to enhance the images captured underwater and degraded due to the medium scattering and absorption. Our method is a single image approach that does not require specialized hardware or knowledge about the underwater conditions or scene structure. It builds on the blending of two images that are directly derived from a color-compensated and white-balanced version of the original degraded image. The two images to fusion, as well as their associated weight maps, are defined to promote the transfer of edges and color contrast to the output image. To avoid that the sharp weight map transitions create artifacts in the low frequency components of the reconstructed image, we also adapt a multiscale fusion strategy. Our extensive qualitative and quantitative evaluation reveals that our enhanced images and videos are characterized by better exposedness of the dark regions, improved global contrast, and edges sharpness. Our validation also proves that our algorithm is reasonably independent of the camera settings, and improves the accuracy of several image processing applications, such as image segmentation and keypoint matching.
Notes: [Ancuti, Codruta O.; Ancuti, Cosmin] Univ Politehn Timisoara, MEO, Timisoara 300023, Romania. [De Vleeschouwer, Christophe] Catholic Univ Louvain, ICTEAM, B-1348 Louvain La Neuve, Belgium. [Bekaert, Philippe] Hasselt Univ, Expertise Ctr Digital Media, B-3590 Hasselt, Belgium.
Keywords: underwater; image fusion; white-balancing;Underwater; image fusion; white-balancing
Document URI: http://hdl.handle.net/1942/26440
ISSN: 1057-7149
e-ISSN: 1941-0042
DOI: 10.1109/TIP.2017.2759252
ISI #: 000414699100016
Rights: © 2017 IEEE. Translations and content mining are permitted for academic research only
Category: A1
Type: Journal Contribution
Validations: ecoom 2018
Appears in Collections:Research publications

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