A Hazy Image Database with Analysis of the Frequency Magnitude

被引：4
|
作者：
Wang, Shuhang [1 ]
Tian, Yu [2 ]
Pu, Tian [3 ]
Wang, Patrick [4 ]
Perner, Petra [5 ]
机构：
[1] Harvard Med Sch, Schepens Eye Res Inst, Mass Eye & Ear, Boston, MA 02114 USA
[2] Beihang Univ, Sch Comp Sci & Engn, Beijing 100083, Peoples R China
[3] Univ Elect Sci & Technol China, Sch Optoelect Informat, Chengdu 610054, Sichuan, Peoples R China
[4] Northeastern Univ, Coll CCIS, Boston, MA 02115 USA
[5] Inst Comp Vis & Appl Comp Sci, Leipzig, Germany
来源：
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE | 2018年 / 32卷 / 05期
关键词：
Image database; haze level; haze removal; natural image statistics; frequency magnitude; QUALITY ASSESSMENT; STATISTICS;
D O I：
10.1142/S0218001418540125
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Image haze removal has been extensively studied, but there has been no such an image database regarding the haze level. It is not convenient for readers to verify the assumptions or priors that are supposed to be useful for haze removal, and meanwhile, it is not fair to compare the performance of haze removal methods, which are effective for images with different haze levels. To solve this problem, we built a database consisting of more than 3464 images of different kinds of outdoor scenes. The images of the database are grouped into four classes regarding the haze level. Along with the database, we also observe a frequency magnitude prior, i.e. the frequency magnitude decreases with the increasing haze level, which can be used as a prior to develop haze removal methods. Our purpose is to help develop image haze removal methods, as well as verify existing statistical priors and discover new ones that can be used for image processing.
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收藏
页数：11
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