[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(5):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(5):404-408.
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CHEN Chen,LI Weijun,CHEN Liang,et al.An adaptive biomimetic image processing method: LDRF algorithm[J].CAAI Transactions on Intelligent Systems,2012,7(5):404-408.
一种自适应的仿生图像增强方法：LDRF算法
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
7
期数:
2012年第5期
页码:
404-408
栏目:
学术论文—机器学习
出版日期:
2012-10-25
- Title:
- An adaptive biomimetic image processing method: LDRF algorithm
- 文章编号:
- 1673-4785(2012)05-0404-05
- Keywords:
- biomimetic image processing; human visual system; image enhancement; triGuassian 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 triGaussian 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:
-
［1］金小贤，李卫军，陈旭，等．一种基于视觉特性的仿生图像增强算法［J］．计算机辅助设计与图形学学报, 2010, 22(3): 534537.
JIN Xiaoxian, LI Weijun, CHEN Xu, et al. An algorithm for biomimetic image enhancement based on human visual property［J］. Journal of ComputerAided Design & Computer Graphics, 2010, 22(3): 534537.
［2］王红梅，李言俊，张科．生物视觉仿生在计算机视觉中的应用研究［J］．计算机应用研究, 2009, 26(3): 11571159.
WANG Hongmei, LI Yanjun, ZHANG Ke. Application of biovision bionics on computer vision［J］. Application Research of Computers, 2009, 26(3): 11571159.
［3］KOLB H. How the retina works［J］. American Scientist, 2003, 91(1): 28.
［4］LAND E H. The retina theory of color vision［J］. Scientific American, 1997, 237(6): 108129.
［5］JOBSON D J, RAHMAN Z, WOODELL G A. Properties and performance of a center/surround retinex［J］. IEEE Transactions on Image Processing, 1997, 6(3): 451462.
［6］ZI Fang, LI Yanjun, ZHAO Dawei, et al. Vision bionics and its application on design of multiwavehand imaging guidance head［J］. Control Technology, 2008, 27(1): 5556.
［7］LI Chaoyi, ZHOU Yixiong, PEI Xing, et al. Extensive disinhibitory region beyond the classical receptive field of cat retinal ganglion cells［J］. Vision Research, 1992, 32(2): 219228.
［8］LI Chaoyi, PEI Xing, ZHOU Yixiong, et al. Role of the extensive area outside the xcell receptive field in brightness information transmission［J］. Vision Research,1991, 31(9): 15291540.
［9］GONZALEZ R C, WOODS R E. Digital image processing［M］. 2nd ed. Upper Saddle River, USA: Prentice Hall, 2002.
［10］PRATT W K. Digital image processing［M］. 4th ed. New York, USA: John Wiley & Sons, 2009: 1669.
［11］CHEN Chen, LI Weijun, CHEN Liang. An improved biomimetic image processing method［C］//Proceedings of the Third International Conference on Artificial Intelligence and Computational Intelligence. Berlin/Heidelberg: SpringerVerlag, 2011: 246254.
［12］WALLIS R H. An approach to the space variant restoration and enhancement of images［C］//Proceedings of Symposium on Current Mathematical Problems in Image Science. Monterey, USA, 1976: 235241.
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