DocumentCode :
3586711
Title :
Quick shift segmentation guided single image haze removal algorithm
Author :
Qingsong Zhu ; Di Wu ; Yaoqin Xie ; Lei Wang
Author_Institution :
Shenzhen Inst. of Adv. Technol., Shenzhen, China
fYear :
2014
Firstpage :
113
Lastpage :
117
Abstract :
This paper presents a novel image haze removal approach from single image. In the algorithm, the constant albedo and dark channel prior methods are combined to represent the transmission model of hazed image. And then, the quick shift segmentation approach is introduced to decompose the input image into some gray level consistent areas. Compared with traditional fixed image partition schemes, better estimation of the atmospheric light can be obtained as well as to avoid the problem of halo artifacts. With the improved haze image modeling approach and atmospheric light estimation, the dehazed image with better visual quality can be achieved.
Keywords :
image colour analysis; image representation; image segmentation; atmospheric light estimation; constant albedo channel prior method; constant dark channel prior method; dehazed image; gray level consistent areas; halo artifact problem avoidance; improved haze image modeling approach; input image decomposition; quick shift segmentation approach; single-image haze removal algorithm; transmission model representation; visual quality; Atmospheric modeling; Computer vision; Conferences; Estimation; Image color analysis; Image segmentation; Mathematical model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Biomimetics (ROBIO), 2014 IEEE International Conference on
Type :
conf
DOI :
10.1109/ROBIO.2014.7090316
Filename :
7090316
Link To Document :
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