A Novel Defogging Algorithm Based on Genetic Algorithm with Analysis of Scientific Data Materials

被引：0
|
作者：
Li, Xiao-Guang [1 ]
Kang, Li [1 ]
机构：
[1] Luoyang Inst Sci & Technol, Luoyang, Peoples R China
来源：
ADVANCED BUILDING MATERIALS AND STRUCTURAL ENGINEERING | 2012年 / 461卷
关键词：
Defogging; Genetic Algorithm; Fitness Function; Scientific Materials;
D O I：
10.4028/www.scientific.net/AMR.461.806
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
This paper proposes a novel defogging algorithm based on the improved model with analysis of scientific data materials. By integrating the merit of genetic algorithm for searching global optimal parameters, the problem of fog-degraded images defogging restoration is transformed into the problem of optimization estimation for original undegraded image by maximizing the global contrast object function, the proposed algorithm can restore the object image as complete as possible in probability sense. Experimental results for single object image defogging gain satisfy visual effect.
引用
收藏
页码：806 / 809
页数：4
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