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Low‐light image haze removal with light segmentation and nonlinear image depth estimation
- Source :
- IET Image Processing, Vol 16, Iss 10, Pp 2623-2637 (2022)
- Publication Year :
- 2022
- Publisher :
- Wiley, 2022.
-
Abstract
- Abstract Hazy image obtained in the low‐light environment has the characteristics of low contrast, non‐uniform illumination, color cast and much noise. In this paper, a method is put forward which can be properly applied to recover low‐light hazy images. The original image is first decomposed into glow layer and haze layer with a modified color channel transformation for glow artifacts and color balanced. A new light segmentation function is proposed next by using gamma correction of channel difference and setting threshold levels to determine if the pixel belongs to light source regions. Then the ambient illuminance map is estimated using maximum reflectance prior to computing the atmosphere light in the light and non‐light regions. Finally, a novel nonlinear image depth estimation model is established to build the relationship between the image depth map and three image features including luminance, saturation and gradient map for the light areas. The experimental results prove that the dehazing algorithm is reliable for removing haze and glow artifacts of active light sources, reducing much noise and improving the visibility.
- Subjects :
- Photography
TR1-1050
Computer software
QA76.75-76.765
Subjects
Details
- Language :
- English
- ISSN :
- 17519667 and 17519659
- Volume :
- 16
- Issue :
- 10
- Database :
- Directory of Open Access Journals
- Journal :
- IET Image Processing
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.9a402db730d34ad2af9118e8b1f11a42
- Document Type :
- article
- Full Text :
- https://doi.org/10.1049/ipr2.12513