Efficient real-time single image dehazing based on color cube constraint

Kponou, Elisee A; Wang, Zhengning; Wei, Ping

doi:10.1109/siprocess.2017.8124515

Cited by 4 publications

(2 citation statements)

References 9 publications

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Section: Flaws In Airlight Estimationmentioning

confidence: 99%

“…Tan in [8] took the maximum intensity value in the hazy image as the value of A, but clearly this would also overestimate A. In [16], airlight A is estimated by taking the maximum of each channel i.e. , but this would also result in overestimation of airlight as it is highly probable that with in an image each channel would have at least one point where channel value is 1 so it is highly probable to get…”

Section: Flaws In Airlight Estimationmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Image Dehazing and Assessment Method

Sami

Muqeet

Tariq

2019

2019 8th International Conference on Information and Communication Technologies (ICICT)

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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.

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Section: Flaws In Airlight Estimationmentioning

confidence: 99%

Section: Flaws In Airlight Estimationmentioning

confidence: 99%