Paper Info
Title
Objective Haze Removal Assessment Based on Two-Objective Optimization
Abstract
Recently, single image haze removal has been investigated extensively. However, its performance is evaluated mainly based on subjective visual quality of recovered images. Several objective assessments have been attempted to evaluate haze removal schemes objectively, such as no-reference image quality model and edge-based assessments. Unfortunately, these objective assessments are not able to measure visual quality of recovered images appropriately, since the visual quality of recovered images is not concerned. Note that an objective assessment for haze removal should consider dehazing effect and distortions introduced during the haze removal process. In this paper, an objective assessment for haze removal based on two-objective optimization is presented where both dehazing effect and distortions of color and artifacts in recovered images are considered. The two indicators are combined with a weighted Euclidean distance. Two examples with two dehazing schemes are provided to justify the proposed objective assessment for haze removal. The simulation indicates that the objective results are consistent with their subjective visual quality of recovered images. It suggests that the proposed objective assessment may be applied to evaluate different haze removal schemes objectively.
Year
DOI
Venue
2017
10.1109/ICAwST.2017.8256463
2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)
Keywords
Field
DocType
haze removal,dark channel,objective assessment,two-objective optimization,weighted Euclidean distance
Computer vision,Visualization,Computer science,Euclidean distance,Image quality,Artificial intelligence,Distortion,Haze
Conference
ISSN
ISBN
Citations 
2325-5986
978-1-5386-2966-6
1
PageRank 
References 
Authors
0.34
4
4
Name
Order
Citations
PageRank
Cheng-Hsiung Hsieh131.07
Shih-Cheng Homg210.34
Zen-Jun Huang310.34
Qiangfu Zhao421462.36