Single image fog removal using anisotropic diffusion

Tripathi, Amrendra; Mukhopadhyay, Sudipta

doi:10.1049/iet-ipr.2011.0472

Cited by 90 publications

(35 citation statements)

References 9 publications

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“…To evaluate the dehazing performance quantitatively, the contrast gain metric C [14] that denotes the mean contrast difference between the dehazed and hazy image is employed to evaluate the capability of haze removal in this letter. Generally, higher value of C means better performance of haze removal method.…”

Section: Quantitative Comparisonmentioning

confidence: 99%

Single Image Haze Removal Using Structure-Aware Atmospheric Veil

Liu

Chen²,

Shang

et al. 2017

IEICE Trans. Inf. & Syst.

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SUMMARYIn this letter, we propose a novel and effective haze removal method by using the structure-aware atmospheric veil. More specifically, the initial atmospheric veil is first estimated based on dark channel prior and morphological operator. Furthermore, an energy optimization function considering the structure feature of the input image is constructed to refine the initial atmospheric veil. At last, the haze-free image can be restored by inverting the atmospheric scattering model. Additionally, brightness adjustment is also performed for preventing the dehazing result too dark. Experimental results on hazy images reveal that the proposed method can effectively remove the haze and yield dehazing results with vivid color and high scene visibility.

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Section: Quantitative Comparisonmentioning

confidence: 99%

Single Image Haze Removal Using Structure-Aware Atmospheric Veil

Liu

Chen²,

Shang

et al. 2017

IEICE Trans. Inf. & Syst.

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“…The goal of the dehaze is to recover J, A and t from I. Among them, the transmission graph t can be expressed as [10]:…”

Section: Dark Channel Priormentioning

confidence: 99%

Retinex Algorithm on Changing Scales for Haze Removal with Depth Map

Wang¹,

Xu²

2014

IJHIT

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“…In addition, this algorithm can work for HSI (hue, saturation and intensity) model which further reduces the computation. It [15] has a wide application in tracking and navigation, consumer electronics and entertainment industries. …”

Section: Anisotropic Diffusion Algorithmmentioning

confidence: 99%