Please use this identifier to cite or link to this item:
Title: A Fast Semi-Inverse Approach to Detect and Remove the Haze from a Single Image
Authors: ANCUTI, Codruta 
ANCUTI, Cosmin 
BEKAERT, Philippe 
Issue Date: 2011
Publisher: Springer Verlag
Source: COMPUTER VISION - ACCV 2010, Pt II.p. 501-514
Series/Report: Lecture Notes in Computer Science
Series/Report no.: 6493
Abstract: In this paper we introduce a novel approach to restore a single image degraded by atmospheric phenomena such as fog or haze. The presented algorithm allows for fast identification of hazy regions of an image, without making use of expensive optimization and refinement procedures. By applying a single per pixel operation on the original image, we produce a 'semi-inverse' of the image. Based on the hue disparity between the original image and its semi-inverse, we are then able to identify hazy regions on a per pixel basis. This enables for a simple estimation of the airlight constant and the transmission map. Our approach is based on an extensive study on a large data set of images, and validated based on a metric that measures the contrast but also the structural changes. The algorithm is straightforward and performs faster than existing strategies while yielding comparative and even better results. We also provide a comparative evaluation against other recent single image dehazing methods, demonstrating the efficiency and utility of our approach
Notes: Reprint Address: Ancuti, CO (reprint author), Hasselt Univ tUL IBBT, Expertise Ctr Digital Media, Wetenschapspark 2, B-3590 Diepenbeek, Belgium Addresses: Hasselt Univ tUL IBBT, Expertise Ctr Digital Media, B-3590 Diepenbeek, Belgium
Keywords: Computer Science, Theory & Methods
Document URI:
ISBN: 978-3-642-19314-9
ISI #: 000295546500039
Category: C1
Type: Proceedings Paper
Validations: ecoom 2012
Appears in Collections:Research publications

Files in This Item:
File Description SizeFormat 
FINAL_ACCV_Dehazing.pdfPreprint5.42 MBAdobe PDFView/Open
Show full item record


checked on May 22, 2022

Page view(s)

checked on May 27, 2022


checked on May 27, 2022

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.