Image Defogging Algorithm Based on Sparse Representation
Joint Authors
Sun, Bo
Fan, Di
Guo, Xinyun
Lu, Xiao
Liu, Xiaoxin
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-11
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Aiming at the problems of low contrast and low definition of fog degraded image, this paper proposes an image defogging algorithm based on sparse representation.
Firstly, the algorithm transforms image from RGB space to HSI space and uses two-level wavelet transform extract features of image brightness components.
Then, it uses the K-SVD algorithm training dictionary and learns the sparse features of the fog-free image to reconstructed I-components of the fog image.
Using the nonlinear stretching approach for saturation component improves the brightness of the image.
Finally, convert from HSI space to RGB color space to get the defog image.
Experimental results show that the algorithm can effectively improve the contrast and visual effect of the image.
Compared with several common defog algorithms, the percentage of image saturation pixels is better than the comparison algorithm.
American Psychological Association (APA)
Fan, Di& Guo, Xinyun& Lu, Xiao& Liu, Xiaoxin& Sun, Bo. 2020. Image Defogging Algorithm Based on Sparse Representation. Complexity،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1143394
Modern Language Association (MLA)
Fan, Di…[et al.]. Image Defogging Algorithm Based on Sparse Representation. Complexity No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1143394
American Medical Association (AMA)
Fan, Di& Guo, Xinyun& Lu, Xiao& Liu, Xiaoxin& Sun, Bo. Image Defogging Algorithm Based on Sparse Representation. Complexity. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1143394
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1143394