随机共振在图像处理中的研究综述
Review of Research on Image Processing Using Stochastic Resonance
DOI: 10.12677/JISP.2015.44016, PDF, HTML, XML, 下载: 2,994  浏览: 8,138  科研立项经费支持
作者: 杨 雪, 李 婷, 杨超琼, 谢佳敏, 罗艺苹, 高仕龙*:乐山师范学院数学与信息科学学院,四川 乐山
关键词: 随机共振图像处理参数调节信息恢复Stochastic Resonance Image Processing Parameter Adjustment Information Retrieval
摘要: 本文综述了随机共振理论在图像处理中已取得的研究成果,并结合已有的基于随机共振理论的图像处理模型,展望了随机共振理论在图像处理中的应用前景。
Abstract: In this paper, the research results of stochastic resonance theory in image processing are summarized. On the basis of the existing image processing model of stochastic resonance theory, the application prospect of stochastic resonance theory in image processing is discussed.
文章引用:杨雪, 李婷, 杨超琼, 谢佳敏, 罗艺苹, 高仕龙. 随机共振在图像处理中的研究综述[J]. 图像与信号处理, 2015, 4(4): 132-138. http://dx.doi.org/10.12677/JISP.2015.44016

参考文献

[1] Benzi, R., Sutera, A. and Vulpiani, A. (1981) The mechanism of stochastic resonance. Journal of Physics A, 14, L453- L457.
http://dx.doi.org/10.1088/0305-4470/14/11/006
[2] Benzi, R., Parisi, G., Sutera, A., et al. (1982) Stochastic resonance in climatic change. Tellus, 34, 10-16.
http://dx.doi.org/10.1111/j.2153-3490.1982.tb01787.x
[3] Fauve, S. and Heslot, F. (1983) Stochastic resonance in bistable system. Physics Letters A, 97, 5-7.
http://dx.doi.org/10.1016/0375-9601(83)90086-5
[4] McNamara, B., Wiesenfeld, K. and Roy, R. (1988) Observation of stochastic resonance in a ring laser. Physics Letters A, 60, 2626-2629.
http://dx.doi.org/10.1103/physrevlett.60.2626
[5] Enrico, S., Massimo, R., Charles, S., et al. (1997) Visual perception of stochastic resonance. Physical Review Letters, 78, 1186-1189.
http://dx.doi.org/10.1103/PhysRevLett.78.1186
[6] Piana, M., Canfora, M. and Riani, M. (2000) Role of noise in image processing by the human perception system. Physical Review E, 68, 1104-1109.
http://dx.doi.org/10.1103/PhysRevE.62.1104
[7] Li, X.F., Cao, G.Z. and Liu, H.J. (2014) Aperiodic signals processing via parameter-tuning stochastic resonance in a photorefractive ring cavity. AIP Advances, 4, Article ID: 047111.
http://dx.doi.org/10.1063/1.4871406
[8] Yang, B.Y., Wang, L.L., et al. (2015) Weak signal detection based on adaptive cascaded bistable stochastic resonance system. Procedia CIRP, 27, 292-297.
http://dx.doi.org/10.1016/j.procir.2015.04.081
[9] Lu, S.L., He, Q.B. and Kong, F.R. (2015) Effects of underdamped step-varying second-order stochastic resonance for weak signal detection. Digital Signal Processing, 36, 93-103.
http://dx.doi.org/10.1016/j.dsp.2014.09.014
[10] 沈伟, 庞全, 范影乐 (2009) 双稳态自适应随机共振的强噪声图像复原研究. 计算机工程与应用, 15, 180-182.
[11] Subramanyam Rallabandi, V.P. and Roy, P.K. (2010) Magnetic resonance image enhancement using stochastic resonance in Fourier domain. Magnetic Resonance Imaging, 28, 1361-1373.
http://dx.doi.org/10.1016/j.mri.2010.06.014
[12] 何朝霞, 刘凯 (2013) 基于Duffing随机共振的图像去噪技术研究. 科学技术与工程, 26, 7683-7687.
[13] Jha, R.K., Chouhan, R., et al. (2014) Dynamic stochastic resonance-based improved logo extraction in discrete cosine transform domain. Computers & Electrical Engineering, 40, 1917-1929.
http://dx.doi.org/10.1016/j.compeleceng.2013.07.024
[14] Liu, J. and Li, Z. (2015) Binary image enhancement based on aperiodic stochastic resonance. IET Image Processing, 7.
http://dx.doi.org/10.1049/iet-ipr.2014.0709
[15] 杨保国, 田坦, 长殿伦 (2011) 双稳态随机共振系统参数选择快速算法及应用. 哈尔滨工业大学学报, 3, 282- 287.
[16] 向学勤, 范影乐, 庞全, 薛凌云 (2009) 基于神经元阈上非周期随机共振机制的灰度图像复原研究. 中国图象图形学报, 1, 77-81.
[17] 庞全, 钱诚, 杨翠容, 范影乐 (2008) 基于双稳态随机共振的图像复原技术研究. 中国图象图形学报, 8, 1447- 1453.
[18] Simonotto, E., et al. (1997) Visual perception of stochastic resonance. Physical Review Letters, 78, 1186-1189.
http://dx.doi.org/10.1103/PhysRevLett.78.1186
[19] 杨异康 (2011) 二维随机共振理论及其在图像处理中的应用. 博士论文, 浙江大学, 杭州.
[20] 陈可, 范影乐, 李轶 (2011) 双稳态随机共振机制及其在图像复原中的应用. 中国图象图形学报, 7, 1170-1177.
[21] 冷永刚, 赵尔华, 石鹏, 张莹 (2011) 二维随机共振参数调节的图像处理. 天津大学学报, 10, 907-913.
[22] 赵尔华 (2012) 图像二维随机共振研究. 硕士论文, 天津大学, 天津.
[23] 曾品善 (2014) 随机共振机制在图像复原中的应用. 科技视界, 34, 180-182.