Open AccessImage defogging based on amended dark channel prior and 4‐directional L 1 regularisation
Author(s) -
Yang Yuliang,
Long Wei,
Li Yanyan,
Shi Xiaoqiu,
Gao Lin
Publication year - 2021
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/ipr2.12233
Subject(s) - channel (broadcasting) , computer science , halo , image (mathematics) , artificial intelligence , range (aeronautics) , transmission (telecommunications) , variable (mathematics) , algorithm , simple (philosophy) , field (mathematics) , computer vision , pattern recognition (psychology) , mathematics , telecommunications , physics , engineering , mathematical analysis , philosophy , epistemology , quantum mechanics , galaxy , pure mathematics , aerospace engineering
The dark channel prior (DCP) algorithm has been widely used in the field of image defogging because of its simple theory and clear restoration result. However, the DCP algorithm has significant limitations. This study clarifies the relationship between halo artfacts and the size of the dark channel patch of the DCP algorithm and analyses the reason why the colour of close‐range white objects appears distorted in the restored images. An amended DCP method is then proposed to solve these problems, utilising a locally variable weighted 4‐directional L 1 regularisation and a corresponding parallel algorithm to optimise the transmission. A deep neural network, 4DL 1 R‐net, is then trained to further enhance the processing speed. Extensive experiments demonstrate that this method is effective. The proposed method can obtain clear details, maintain the natural clarity of images, and achieve significant improvements over state‐of‐the‐art methods.