自适应随机共振技术在图像复原中的应用*

作者：吴舜,庞全,向学勤 日期：2009-04-21/span> 浏览：3772 查看PDF文档

自适应随机共振技术在图像复原中的应用*

吴舜,庞全,向学勤
(杭州电子科技大学 生物医学工程与仪器研究所,浙江 杭州 310018)

摘要：为了优化强噪声背景下图像复原的效果，将随机共振原理应用于图像复原。通过添加最佳噪声的方法来实现随机共振，从而达到比较满意的复原效果，并提出了一种自适应算法。实验结果表明，在信噪比很低时，该方法优于传统方法，为强背景噪声下的图像复原、目标识别和图像理解等应用提供了一种新的思路。
关键词：随机共振；图像复原；自适应；峰值信噪比
中图分类号：TP391.41文献标识码：A文章编号：1001-4551(2009)03-0009-03

Application of self-adaptive stochastic resonance on image restoration
WU Shun, PANG Quan, XIANG Xue-qin
(Institute of Biomedical Engineering and Instrument, Hangzhou Dianzi University, Hangzhou 310018, China)
Abstract: Aiming at achieving better result of image restoration under strong noise background, stochastic resonance principle was applied to image restoration. By means of adding optimal noise, stochastic resonance and the better result of image restoration were achieved. And a self-adaptive stochastic resonance algorithm was provided. Results indicate that, as to the restoration effect of gray-scale noisy image, especially low PSNR, the new method is better than typical methods. A kind of method for such engineering application as image restoration, target diction and visual understanding is provided.
Key words: stochastic resonance（SR）; image restoration; self-adaptive; power signal-to-noise ratio（PSNR）
参考文献(References):
［1］LAZZARO D, MONTEFUSCO L B. Edge-preserving wavelet thresholding for image denoising［J］. Journal of Computational and Applied Mathematics,2006,11(19):274-278.
［2］LENG Yong-gang, WANG Tai-yong. Numerial research of twice sampling stochastic resonance for the detection of a weak signal submerged in a heavy noise［J］. Acta Physica Sinica,2003,521(10):2432-2437.
［3］LENG Yong-gang, WANG Tai-yong. Scale transformation stochastic resonance for the monitoring and diagnosis of electromotor faults［J］. Proceedings of the Chinese Society of Electrical Engineering,2003,23(11):111-115.
［4］KIM Y, MARCIA G, SATORU S. Stochastic resonance in binocular rivalry［J］. Vision Research,2006,46(3):392-406.
［5］PIANA M, CANFORA M, RIANI M. Role of noise in image processing by human perceptive system［J］. Physics Review Letters,2000,62(1):1104-1109.
［6］YANG T. Adaptively optimizing stochastic resonance in visual system［J］. Phys Lett A,1998,245(1):79-86.
［7］XU Bo-hou, LI Jian-long, ZHENG Jin-yang. Parameter-induced aperiodic stochastic resonance in the presence of mutilicative noise and additive noise［J］. Physica A,2004,343（11）:156-166.
［8］何大海，赵文礼，梅晓俊.基于随机共振原理的微弱信号检测与应用[J].机电工程，2008，25（4）：71-74.