Fuzzy Adaptive Gamma Correction for Contrast Enhancement

被引:0
|
作者
Parihar, Anil Singh [1 ]
机构
[1] Delhi Technol Univ, Dept Informat Technol, Delhi, India
来源
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTELLIGENT SUSTAINABLE SYSTEMS (ICISS 2017) | 2017年
关键词
fuzzy logic; membership function; gamma correctio; contrast enhancement; DYNAMIC HISTOGRAM EQUALIZATION; IMAGE-ENHANCEMENT;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a new contrast enhancement algorithm based on fuzzy logic. The fuzzy contrast distribution (FCD) is introduced in this work. The algorithm computes FCD of the input image using fuzzy membership function and fuzzy rules. An adaptive parameter gamma is defined using FCD. The algorithm uses gamma correction with adaptive gamma to obtain the contrast-enhanced images. The performance of the proposed algorithm is compared with conventional as well as state-of-art contrast enhancement algorithms. The assessment of the experimental results is performed quantitatively and visually. The assessment of results shows that the proposed algorithm outperforms most of the existing contrast enhancement algorithms. The proposed algorithm yields good contrast, natural-looking images.
引用
收藏
页码:625 / 629
页数:5
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