An Improved Defogging Algorithm Based on Dark Color Theory Combined with Self-Adaptive Threshold Mechanism. (1st August 2018)
- Record Type:
- Journal Article
- Title:
- An Improved Defogging Algorithm Based on Dark Color Theory Combined with Self-Adaptive Threshold Mechanism. (1st August 2018)
- Main Title:
- An Improved Defogging Algorithm Based on Dark Color Theory Combined with Self-Adaptive Threshold Mechanism
- Authors:
- Li, Aixing
Fang, Zhou
Mi, Bo - Other Names:
- Zhao Yun-Bo Academic Editor.
- Abstract:
- Abstract : Defogging algorithms based on dark channel prior have color shift in light color areas because of inaccurate estimation of transmittance. To resolve this problem, a novel improved image clearness method is proposed. Based on the dark channel prior, the essential causes of color shift are analyzed, with two important factors summarized. Then, transmission map is calculated by using 3⁎ 3 fixed region, and the restoration module based on self-adaptive threshold mechanism for transmission map is provided. Some experiments are carried out to determine parameters in restoration module to correct the transmission map. According to the corrected transmission map, a transmission restoration algorithm is constructed based on the self-adaptive threshold mechanism to improve the performance of the fog-free image. The experiment results show that this method can resolve the color shift in light color areas effectively and guarantee the overall framework of defogging method based on dark color theory unchanged.
- Is Part Of:
- Journal of control science and engineering. Volume 2018(2018)
- Journal:
- Journal of control science and engineering
- Issue:
- Volume 2018(2018)
- Issue Display:
- Volume 2018, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 2018
- Issue:
- 2018
- Issue Sort Value:
- 2018-2018-2018-0000
- Page Start:
- Page End:
- Publication Date:
- 2018-08-01
- Subjects:
- Control theory -- Periodicals
629.831205 - Journal URLs:
- https://www.hindawi.com/journals/jcse/ ↗
- DOI:
- 10.1155/2018/3975373 ↗
- Languages:
- English
- ISSNs:
- 1687-5249
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 10428.xml