Paper Info
Title
Quick shift segmentation guided single image haze removal algorithm
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.
Year
DOI
Venue
2014
10.1109/ROBIO.2014.7090316
ROBIO
Keywords
Field
DocType
image representation,constant dark channel prior method,input image decomposition,gray level consistent areas,image segmentation,halo artifact problem avoidance,atmospheric light estimation,constant albedo channel prior method,transmission model representation,improved haze image modeling approach,dehazed image,quick shift segmentation approach,single-image haze removal algorithm,image colour analysis,visual quality,atmospheric modeling,computer vision,mathematical model,estimation
Computer vision,Scale-space segmentation,Feature detection (computer vision),Image texture,Binary image,Image processing,Algorithm,Image quality,Image segmentation,Artificial intelligence,Engineering,Image restoration
Conference
Citations 
PageRank 
References 
0
0.34
16
Authors
4
Name
Order
Citations
PageRank
Qingsong Zhu111613.96
Di Wu2636117.73
Yaoqin Xie312521.70
Lei Wang4252.48