[1]谌琛,李卫军,陈亮,等.一种自适应的仿生图像增强方法:LDRF算法[J].智能系统学报,2012,7(05):404-408.
 CHEN Chen,LI Weijun,CHEN Liang,et al.An adaptive biomimetic image processing method: LDRF algorithm[J].CAAI Transactions on Intelligent Systems,2012,7(05):404-408.
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一种自适应的仿生图像增强方法:LDRF算法(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第7卷
期数:
2012年05期
页码:
404-408
栏目:
出版日期:
2012-10-25

文章信息/Info

Title:
An adaptive biomimetic image processing method: LDRF algorithm
文章编号:
1673-4785(2012)05-0404-05
作者:
谌琛李卫军陈亮覃鸿来疆亮
中国科学院半导体研究所 神经网络实验室,北京 100083
Author(s):
CHEN Chen LI Weijun CHEN Liang QIN Hong LAI Jiangliang 
Laboratory of Artificial Neural Networks, Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China
关键词:
仿生图像处理人类视觉图像增强三高斯模型参数对数模型增益因子模型
Keywords:
biomimetic image processing human visual system image enhancement triGuassian model parameterized logarithmic model gain factor model
分类号:
TP391.4
文献标志码:
A
摘要:
为了研究基于人类视觉系统特性(亮度自适应特性和视网膜神经元感受野非经典侧抑制特性)的仿生图像处理方法,增强仿生图像增强算法的自适应性,提出了一种新的自适应仿生图像增强算法——LDRF算法.LDRF算法首先建立参数对数模型对图像全局亮度进行自适应调整,然后采用三高斯动态滤波进行局部细节增强,引入Wallis算子建立增益因子模型,使局部细节增强具有自适应性,最后通过线性变换恢复图像彩色信息.在大量图像上进行对比实验和分析.实验结果证明,LDRF算法能够避免过增强现象,并且针对不同大小、不同内容的图像能够自适应地进行图像增强,取得了较好的效果,提高了仿生图像增强算法的实用性.
Abstract:
The research proposes to continue examining a novel adaptive biomimetic image processing method called, LDRF (logarithmic and disinhibitory properties of concentric receptive field) algorithm. Numerous research studies have examined biomimetic image processing method and human visual characteristics, which include brightness adaptability and disinhibitory properties of concentric receptive fields. Firstly, a parameterize logarithmic function was adjusted for global luminance for image adaptability. Secondly, the triGaussian dynamic filtering was applied to the partial detail enhancement. Wallis operator was also introduced for establishing a gain factor model that provided adaptability for partial detail enhancement as well. Finally, the linear transform was performed for the color restoration. The contrast experimental results were based on a large image set which indicated, the LDRF algorithm is capable of adapting and enhancing the images with different sizes and contents. Additionally, the study avoided over enhancement, achieved excellent effects and increased practicality of the biomimetic image enhancement algorithm.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2012-04-03.
网络出版日期:2012-09-07.
基金项目:〖国家自然科学基金重大研究项目(90920013). 
通信作者:李卫军.
E-mail: wjli@semi.ac.cn.
作者简介:
谌琛,女,1987年生,硕士研究生,主要研究方向为图像处理与模式识别.  
李卫军,男,1975年生,副研究员,博士,主要研究方向为图像处理与模式识别.主持国家“863”计划项目1项、国家自然科学基金重大研究计划项目1项.获得发明专利3项,发表学术论文20余篇.
 陈亮,男,1988年生,硕士研究生,主要研究方向为图像处理与模式识别.
更新日期/Last Update: 2012-11-13