Open AccessReal‐time single image dehazing using block‐to‐pixel interpolation and adaptive dark channel prior
Author(s) -
Yu Teng,
Riaz Irfan,
Piao Jingchun,
Shin Hyunchul
Publication year - 2015
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2015.0087
Subject(s) - computer science , channel (broadcasting) , pixel , block (permutation group theory) , interpolation (computer graphics) , artificial intelligence , computation , transmission (telecommunications) , computer vision , noise (video) , gaussian , algorithm , image (mathematics) , mathematics , physics , telecommunications , geometry , quantum mechanics
The authors propose a novel and efficient method for single image dehazing. To accelerate the transmission estimation process, a block‐to‐pixel interpolation method is used for fine dark channel computation, in which the block‐level dark channel is first computed, and then the fine pixel‐level dark channel is obtained by a weighted voting of the block‐level dark channel to preserve edges and smooth out texture noise. This technique can be used for a direct transmission map generation without a computationally expensive refinement step. Since the dark channel prior (DCP) is not valid in bright (sky) regions, they propose an adaptive DCP modelled by a Gaussian curve that produces a more natural recovered image of the sky and other bright regions. In addition, a scaling method for transmission map computation is proposed to further accelerate the dehazing method. Through experiments, they show that the proposed adaptive block‐to‐pixel technique is about 30 times faster and produces improved recovered images than the well‐known state‐of‐the‐art DCP approach.