scholarly journals Real-time hardware accelerator for single image haze removal using dark channel prior and guided filter

2014 ◽  
Vol 11 (24) ◽  
pp. 20141002-20141002 ◽  
Author(s):  
Zhengfa Liang ◽  
Hengzhu Liu ◽  
Botao Zhang ◽  
Benzhang Wang
Keyword(s):  
Real Time ◽  
Guided Filter ◽  
Hardware Accelerator ◽  
Dark Channel Prior ◽  
Single Image ◽  
Haze Removal ◽  
Dark Channel

Accelerated haze removal for a single image by dark channel prior

2019 ◽  
Vol 20 (8) ◽  
pp. 1109-1118 ◽  
Author(s):  
Bo-xuan Yue ◽  
Kang-ling Liu ◽  
Zi-yang Wang ◽  
Jun Liang
Keyword(s):  
Dark Channel Prior ◽  
Single Image ◽  
Haze Removal ◽  
Dark Channel

scholarly journals Real-Time Haze Removal Using Normalised Pixel-Wise Dark-Channel Prior and Robust Atmospheric-Light Estimation

2020 ◽  
Vol 10 (3) ◽  
pp. 1165 ◽  
Author(s):  
Yutaro Iwamoto ◽  
Naoaki Hashimoto ◽  
Yen-Wei Chen
Keyword(s):  
Real Time ◽  
Computational Cost ◽  
Dark Channel Prior ◽  
Detailed Structure ◽  
Haze Removal ◽  
Acceptable Quality ◽  
Colour Channel ◽  
Dark Channel ◽  
High Computational Cost ◽  
Atmospheric Light

This study proposes real-time haze removal from a single image using normalised pixel-wise dark-channel prior (DCP). DCP assumes that at least one RGB colour channel within most local patches in a haze-free image has a low-intensity value. Since the spatial resolution of the transmission map depends on the patch size and it loses the detailed structure with large patch sizes, original work refines the transmission map using an image-matting technique. However, it requires high computational cost and is not adequate for real-time application. To solve these problems, we use normalised pixel-wise haze estimation without losing the detailed structure of the transmission map. This study also proposes robust atmospheric-light estimation using a coarse-to-fine search strategy and down-sampled haze estimation for acceleration. Experiments with actual and simulated haze images showed that the proposed method achieves real-time results of visually and quantitatively acceptable quality compared with other conventional methods of haze removal.

Haze Removal for a Single Image Using Adaptive Template Dark Channel Prior

2014 ◽  
Vol 543-547 ◽  
pp. 2480-2483
Author(s):  
Jing Zhang ◽  
Wei Dong ◽  
Juan Li ◽  
Xu Ning Liu
Keyword(s):  
Input Image ◽  
Dark Channel Prior ◽  
Edge Region ◽  
Single Image ◽  
Haze Removal ◽  
Flat Region ◽  
Imaging Model ◽  
Texture Region ◽  
Dark Channel ◽  
Single Input

In this paper, we propose an adaptive template method based on the dark channel prior. The method combines with the haze imaging model to haze removal for a single image. This method can effectively remove haze from a single input image. According to the characteristics of the image itself and the haze removal effect of the different template we divide the input image into flat region, edge region and texture region. Then, select the lager size template dispose the flat region and use midrange or minitype template dispose the edge region and texture area. Experimental results demonstrate that the proposed algorithm has very good performance for fog removal and retains the image details more effectively.

Saliency-based dark channel prior model for single image haze removal

2018 ◽  
Vol 12 (6) ◽  
pp. 1049-1055 ◽  
Author(s):  
Libao Zhang ◽  
Shiyi Wang ◽  
Xiaohan Wang
Keyword(s):  
Dark Channel Prior ◽  
Single Image ◽  
Prior Model ◽  
Haze Removal ◽  
Dark Channel
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