Technical Papers Session III: A novel image dehazing and assessment method
Abstract/Description
Images captured in hazy weather conditions often suffer from color contrast and color fidelity. This degradation is represented by transmission map which represents the amount of attenuation and airlight which represents the color of additive noise. In this paper, we have proposed a method to estimate the transmission map using haze levels instead of airlight color since there are some ambiguities in estimation of airlight. Qualitative and quantitative results of proposed method show competitiveness of the method given. In addition we have proposed two metrics which are based on statistics of natural outdoor images for assessment of haze removal algorithms.
Keywords
Haze removal, Image quality assessment, Atmospheric scattering, Airlight co-efficient map and computer vision
Location
Room C9 (Aman Tower, 3rd floor)
Session Theme
Technical Papers Session III - Computer Vision
Session Type
Parallel Technical Session
Session Chair
Dr. Asim Ur Rehman Khan
Start Date
16-11-2019 3:10 PM
End Date
16-11-2019 3:30 PM
Recommended Citation
Sami, S. B., Muqeet, A., & Tariq, H. (2019). Technical Papers Session III: A novel image dehazing and assessment method. International Conference on Information and Communication Technologies. Retrieved from https://ir.iba.edu.pk/icict/2019/2019/20
COinS
Technical Papers Session III: A novel image dehazing and assessment method
Room C9 (Aman Tower, 3rd floor)
Images captured in hazy weather conditions often suffer from color contrast and color fidelity. This degradation is represented by transmission map which represents the amount of attenuation and airlight which represents the color of additive noise. In this paper, we have proposed a method to estimate the transmission map using haze levels instead of airlight color since there are some ambiguities in estimation of airlight. Qualitative and quantitative results of proposed method show competitiveness of the method given. In addition we have proposed two metrics which are based on statistics of natural outdoor images for assessment of haze removal algorithms.
