Abstract
In this paper, recent pulse coupled neural networks (PCNN) model’s development, especially in the fields related to the image processing, were surveyed. Our review aims to provide a comprehensive and systematic analysis of selected researches from past few decades, having powerful methods to infer the area of study. In this paper, all selected references are categorized in three groups, on the basis of neurons structure, parameters setting, and the inherent characteristics of PCNN. Various applications of these models were mentioned and underlying difficulties, limitations, merits and disadvantages were discussed in applying these models. The researchers will find it helpful to choose and use the appropriate model for a better application.
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References
Gray CM, Singer W (1989) Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex. Proc Nat Acad Sci 86(5):1698–1702
Reinhard E, Reitboeck HJ, Arndt M, Dicke P (1990) Feature linking via synchronization among distributed assemblies: simulations of results from cat visual cortex. Neural Comput 2(3):293–307
Reitboeck HJ, Eckhorn R, Arndt M, Dicke P (1990) A model for feature linking via correlated neural activity. In Synergetics of Cognition, pages 112–125. Springer
Johnson JL, Ritter D (1993) Observation of periodic waves in a pulse-coupled neural network. Opt Lett 18(15):1253–1255
Johnson JL (1994) Pulse-coupled neural nets: translation, rotation, scale, distortion, and intensity signal invariance for images. Appl Opt 33(26):6239–6253
Ranganath HS, Kuntimad G, Johnson JL (1995) Pulse coupled neural networks for image processing. In: Proceedings IEEE Southeastcon’95. Visualize the future. IEEE, pp 37–43
Jason M Kinser (1996) Simplified pulse-coupled neural network. In: Aerospace/defense sensing and controls, international society for optics and photonics. pp 563–567
Johnson JL, Padgett ML (1999) PCNN models and applications. IEEE Trans Neural Netw 10(3):480–498
Ulf E, Kinser JM, Atmer J, Zetterlund N (2004) The intersecting cortical model in image processing. Nucl Instrum Methods Phys Res Sect A 525(1):392–396
Zhan K, Zhang H, Ma Y (2009) New spiking cortical model for invariant texture retrieval and image processing. IEEE Trans Neural Netw 20(12):1980–1986
Huang Y, Ma Y, Li S, Zhan K (2016) Application of heterogeneous pulse coupled neural network in image quantization. J Electron Imaging 25(6):061603–061603
Yang Z, Dong M, Guo Y, Gao X, Wang K, Shi B, Ma Y (2016) A new method of micro-calcifications detection in digitized mammograms based on improved simplified PCNN. Neurocomputing 218:79–90
Thomas L, Kinser JM, Lindblad T, Kinser JM (1998) Image processing using pulse-coupled neural networks. Springer, Berlin
Xiaodong G, Daoheng Y, Zhang L (2005) Image shadow removal using pulse coupled neural network. IEEE Trans Neural Netw 16(3):692–698
Gu X, Zhang L, Yu D (2005) General design approach to unit-linking PCNN for image processing. In: Proceedings 2005 IEEE international joint conference on neural networks, 2005. IJCNN’05, vol 3, IEEE, pp 1836–1841
Chen Y, Park S-K, Ma Y, Ala R (2011) A new automatic parameter setting method of a simplified PCNN for image segmentation. IEEE Trans Neural Netw 22(6):880–892
Deng X, Ma Y (2012) PCNN model automatic parameters determination and its modified model. Acta Electron Sin 40(5):955–964
Ma Y, Wang Z, Zheng JZ, Lu L, Wang G, Li P, Ma T, Xie Y (2006) Extracting micro-calcification clusters on mammograms for early breast cancer detection. In: 2006 IEEE international conference on information acquisition. IEEE, pp 499–504
Beer RD, Chiel HJ, Sterling LS (1989) Heterogeneous neural networks for adaptive behavior in dynamic environments. Adv Neural Inf Process Syst 577–585
Selverston AI (1988) A consideration of invertebrate central pattern generators as computational data bases. Neural Netw 1(2):109–117
Kuffler Stephen W, Nicholls John G, Martin AR (1976) A cellular approach to the function of the nervous system. Sinauer Associates, Massachusetts
Huang Y, Ma Y, Li S (2015) A new method for image quantization based on adaptive region related heterogeneous PCNN. In: International symposium on neural networks, Springer, pp 269–278
Ma Y, Liu L, Zhan K, Yongqing W (2010) Pulse-coupled neural networks and one-class support vector machines for geometry invariant texture retrieval. Image Vis Comput 28(11):1524–1529
Szekely G, Lindblad T (1999) Parameter adaptation in a simplified pulse-coupled neural network. In: Ninth workshop on virtual intelligence/dynamic neural networks: neural networks fuzzy systems, evolutionary systems and virtual re, international society for optics and photonics, pp 278–285
Yi-De M, Ro-Lan D, Lian L (2001) A new algorithm of image segmentation based on pulse-coupled neural networks and the entropy of images. In: Proceeding international conference neural information processing
Kuntimad G, Ranganath HS (1999) Perfect image segmentation using pulse coupled neural networks. IEEE Trans Neural Netw 10(3):591–598
Karvonen JA (2004) Baltic sea ice sar segmentation and classification using modified pulse-coupled neural networks. IEEE Trans Geosci Remote Sens 42(7):1566–1574
Stewart RD, Fermin I, Opper M (2002) Region growing with pulse-coupled neural networks: an alternative to seeded region growing. IEEE Trans Neural Netw 13(6):1557–1562
Ma Y, Qi CL (2006) Study of automated PCNN system based on genetic algorithm. J Syst Simul 18(3):722–725
Yonekawa M, Kurokawa H (2009) An automatic parameter adjustment method of pulse coupled neural network for image segmentation. Artif Neural Netw ICANN 2009:834–843
Bi Y, Qiu T, Li X, Guo Y (2004) Automatic image segmentation based on a simplified pulse coupled neural network. In: International symposium on neural networks. Springer, pp 405–410
Yi-de M, Qing L, Zhi-Bai Q (2004) Automated image segmentation using improved PCNN model based on cross-entropy. In: Proceedings of 2004 international symposium on intelligent multimedia, video and speech processing, 2004. IEEE, pp 743–746
Ma Y-D, Dai R, Li L (2002) Automated image segmentation using pulse coupled neural networks and image’s entropy. J China Inst Commun 23(1):46–51
Chen Y, Ma Y, Kim DH, Park S-K (2015) Region-based object recognition by color segmentation using a simplified PCNN. IEEE Transact Neural Netw Learn Syst 26(8):1682–1697
Shi M, Jiang S, Wang H, Bugao X (2009) A simplified pulse-coupled neural network for adaptive segmentation of fabric defects. Mach Vis Appl 20(2):131–138
Rava TH, Rava TH, Bettaiah V, Ranganath HS (2011) Adaptive pulse coupled neural network parameters for image segmentation. World Acad Sci Eng Technol 73:1046–1052
Tsuda I (2001) Toward an interpretation of dynamic neural activity in terms of chaotic dynamical systems. Behav Brain Sci 24(05):793–810
Yamaguchi Y, Ishimura K, Wada M (2002) Synchronized oscillation and dynamical clustering in chaotic PCNN. In: Proceedings of the 41st SICE annual conference SICE 2002, vol 2, IEEE, pp 730–735
Yamaguchi Y, Ishimura K, Wada M (2002) Chaotic pulse-coupled neural network as a model of synchronization and desynchronization in cortex. In: Proceedings of the 9th international conference on neural information processing, 2002. ICONIP’02, vol 2, IEEE, pp 571–575
Wang X, Zhi-jian XU, Lian-feng LI et al (2009) Chaos control based on pulse-coupled neural networks. J Comput Appl 29(12):3277–3279
Kinser JM, Nguyen C (2000) Image object signatures from centripetal autowaves. Pattern Recogn Lett 21(3):221–225
Zhan K, Teng J, Shi J, Li Q, Wang M (2016) Feature-linking model for image enhancement. Neural Comput 28(6):1072
Tolba MF, Abdellwahab MS, Aboul-Ela M, Samir A (2010) Image signature improving by PCNN for arabic sign language recognition. Can J Artif Intell Mach Learn Pattern Recognit 1(1):1–6
Elons SA, Abull-Ela M, Fahmy Tolba M (2013) A proposed PCNN features quality optimization technique for pose-invariant 3d arabic sign language recognition. Appl Soft Comput 13(4):1646–1660
Tolba MF, Samir A, Aboul-Ela M (2013) Arabic sign language continuous sentences recognition using PCNN and graph matching. Neural Comput Appl 23(3–4):999–1010
Nie R, Zhou D, He M, Jin X, Yu J (2015) Facial feature extraction using frequency map series in PCNN. J Sens 2016(4):1–9
Jin X, Nie R, Zhou D, Yao S, Chen Y, Jiefu Y, Wang Q (2016) A novel dna sequence similarity calculation based on simplified pulse-coupled neural network and huffman coding. Phys A 461:325–338
Mureşan RC (2003) Pattern recognition using pulse-coupled neural networks and discrete fourier transforms. Neurocomputing 51:487–493
Wang C, Zhou J, Qin H, Li C, Zhang Y (2011) Fault diagnosis based on pulse coupled neural network and probability neural network. Expert Syst Appl 38(11):14307–14313
Samir A, Elons SA, Abull-ela M, Tolba MF (2013) Neutralizing lighting non-homogeneity and background size in PCNN image signature for arabic sign language recognition. Neural Comput Appl 22(1):47–53
Ma Y, Dai R, Li L, Wei L (2002) Image segmentation of embryonic plant cell using pulse-coupled neural networks. Chin Sci Bull 47(2):169–173
Yunfeng L, Miao J, Duan L, Qiao Y, Jia R (2008) A new approach to image segmentation based on simplified region growing PCNN. Appl Math Comput 205(2):807–814
Wei S, Hong Q, Hou M (2011) Automatic image segmentation based on PCNN with adaptive threshold time constant. Neurocomputing 74(9):1485–1491
Karina W, Thomas L, Vlatko B, Guillen JLL, Klingner PL (2000) Patterns from the sky: satellite image analysis using pulse coupled neural networks for pre-processing, segmentation and edge detection. Pattern Recogn Lett 21(3):227–237
Del Frate F, Latini D, Pratola C, Palazzo F (2013) PCNN for automatic segmentation and information extraction from x-band sar imagery. International Journal of Image and Data Fusion 4(1):75–88
Li Z, Liu Y, Walker R, Hayward R, Zhang J (2010) Towards automatic power line detection for a uav surveillance system using pulse coupled neural filter and an improved hough transform. Mach Vis Appl 21(5):677–686
Na YANG, Houjin CHEN, Yanfeng LI, Xiaoli HAO (2012) Coupled parameter optimization of PCNN model and vehicle image segmentation. J Transp Syst Eng Inf Technol 12(1):48–54
Li H, Jin X, Yang N, Yang Z (2015) The recognition of landed aircrafts based on PCNN model and affine moment invariants. Pattern Recogn Lett 51:23–29
Wang X, Lei L, Wang M (2012) Palmprint verification based on 2d-gabor wavelet and pulse-coupled neural network. Knowl Based Syst 27:451–455
Sugiyama T, Homma N, Abe K, Sakai M (2004) Speech recognition using pulse-coupled neural networks with a radial basis function. Artif Life Robot 7(4):156–159
Li H, Guo L, Yu P, Chen J, Tang Y (2016) Image segmentation based on iterative self-organizing data clustering threshold of PCNN. In: 2016 2nd international conference on cloud computing and internet of things (CCIOT), IEEE, pp 73–77
Chou N, Jiarong W, Bingren JB, Qiu A, Chuang K-H (2011) Robust automatic rodent brain extraction using 3-d pulse-coupled neural networks (PCNN). IEEE Trans Image Process 20(9):2554–2564
Hassanien AE, Al-Qaheri H, El-Dahshan E-SA (2011) Prostate boundary detection in ultrasound images using biologically-inspired spiking neural network. Appl Soft Comput 11(2):2035–2041
Li J, Zou B, Ding L, Gao X (2013) Image segmentation with PCNN model and immune algorithm. JCP 8(9):2429–2436
Xu X, Liang T, Wang G, Wang M, Wang X (2017) Self-adaptive PCNN based on the ACO algorithm and its application on medical image segmentation. Intell Autom Soft Comput 23(2):303–310
Lian J, Ma Y, Ma Y, Shi B, Liu J, Yang Z, Guo Y (2017) Automatic gallbladder and gallstone regions segmentation in ultrasound image. Int J Comput Ass Radiol Surg 12(4):1–16
Guo Y, Dong M, Yang Z, Gao X, Wang K, Luo C, Ma Y, Zhang J (2016) A new method of detecting micro-calcification clusters in mammograms using contourlet transform and non-linking simplified PCNN. Comput Methods Programs Biomed 130:31–45
Wang L, Li S, Chen R, Liu S-Y, Chen J-C (2016) An automatic segmentation and classification framework based on PCNN model for single tooth in microct images. PLoS ONE 11(6):e0157694
Tang J, Zhang N, Li D, Wang F, Zhang B, Wang C, Shen C, Ren J, Xue C, Liu J (2016) Novel robust skylight compass method based on full-sky polarization imaging under harsh conditions. Opt Express 24(14):15834–15844
Ruan C, Dean Zhao X, Chen WJ, Liu X (2016) Aquatic image segmentation method based on hs-PCNN for automatic operation boat in crab farming. J Comput Theor Nanosci 13(10):7366–7374
Wang B, Wan L, Li Y (2016) Saliency motivated pulse coupled neural network for underwater laser image segmentation. J Shanghai Jiaotong Univ (Sci) 21:289–296
Ma Y, Lin D, Zhang B, Liu Q, Gu J (2007) A novel algorithm of image gaussian noise filtering based on PCNN time matrix. In: IEEE international conference on signal processing and communications, 2007 ICSPC 2007. IEEE, pp 1499–1502
Zou B, Zhou H, Chen H, Shi C (2012) Multi-channel image noise filter based on PCNN. JCP 7(2):475–482
Yi-de M, Fei S, Lian L (2003) A new kind of impulse noise filter based on PCNN. In: Proceedings of the 2003 international conference on neural networks and signal processing, 2003, vol 1, IEEE, pp 152–155
Hong-juan Z, Zong-nian Z, Dong-mei L, Yi-de M (2007) A novel image de-noising algorithm combined PCNN with morphology. In: International symposium on intelligent signal processing and communication systems, 2007. ISPACS 2007. IEEE, pp 208–211
Deng X, Ma Y, Dong M (2016) A new adaptive filtering method for removing salt and pepper noise based on multilayered PCNN. Pattern Recogn Lett 79:8–17
Shen C, Wang D, Tang S, Cao H, Liu J (2017) Hybrid image noise reduction algorithm based on genetic ant colony and PCNN. Visual Comput 33(11):1373–1384
Kinser JM (1997) Pulse-coupled image fusion. Opt Eng 36(3):737–742
Broussard RP, Rogers SK, Oxley ME, Tarr GL (1999) Physiologically motivated image fusion for object detection using a pulse coupled neural network. IEEE Trans Neural Networks 10(3):554–563
Li M, Cai W, Tan Z (2006) A region-based multi-sensor image fusion scheme using pulse-coupled neural network. Pattern Recogn Lett 27(16):1948–1956
Huang W, Jing Z (2007) Multi-focus image fusion using pulse coupled neural network. Pattern Recogn Lett 28(9):1123–1132
Qu X, Hu C, Yan J (2008) Image fusion algorithm based on orientation information motivated pulse coupled neural networks. In: 7th world congress on intelligent control and automation, 2008. WCICA 2008. IEEE, pp 2437–2441
Chai Y, Li HF, Guo MY (2011) Multifocus image fusion scheme based on features of multiscale products and PCNN in lifting stationary wavelet domain. Opt Commun 284(5):1146–1158
Xiao-Bo Q, Jing-Wen Y, Hong-Zhi XIAO, Zi-Qian Z (2008) Image fusion algorithm based on spatial frequency-motivated pulse coupled neural networks in nonsubsampled contourlet transform domain. Acta Autom Sin 34(12):1508–1514
Yang S, Wang M, YanXiong L, Qi W, Jiao L (2009) Fusion of multiparametric sar images based on sw-nonsubsampled contourlet and PCNN. Sig Process 89(12):2596–2608
Yang S, Wang M, Jiao L, Ruixia W, Wang Z (2010) Image fusion based on a new contourlet packet. Inf Fus 11(2):78–84
Kavitha CT, Chellamuthu C, Rajesh R (2012) Medical image fusion using combined discrete wavelet and ripplet transforms. Proc Eng 38:813–820
Yang S, Wang M, Jiao L (2012) Contourlet hidden markov tree and clarity-saliency driven PCNN based remote sensing images fusion. Appl Soft Comput 12(1):228–237
Baohua Z, Xiaoqi L, Weitao J (2013) A multi-focus image fusion algorithm based on an improved dual-channel PCNN in nsct domain. Opt Int J Light Electron Opt 124(20):4104–4109
Wang N, Ma Y, Zhan K, Yuan M (2013) Multimodal medical image fusion framework based on simplified PCNN in nonsubsampled contourlet transform domain. J Multimed 8(3):270–276
Kong W, Zhang L, Lei Y (2014) Novel fusion method for visible light and infrared images based on NSST-SF-PCNN. Infrared Phys Technol 65:103–112
Wang J, Li Q, Jia Z, Kasabov N, Yang J (2015) A novel multi-focus image fusion method using PCNN in nonsubsampled contourlet transform domain. Opt Int J Light Electron Opt 126(20):2508–2511
Xiang T, Yan L, Gao R (2015) A fusion algorithm for infrared and visible images based on adaptive dual-channel unit-linking PCNN in nsct domain. Infrared Phys Technol 69:53–61
Ganasala P, Kumar V (2016) Feature-motivated simplified adaptive PCNN-based medical image fusion algorithm in NSST domain. J Digit Imaging 29(1):73–85
Jia Y, Rong C, Zhu Y, Yang Y, Wang Y (2016) A novel image fusion algorithm using PCNN in nsct domain. In: International congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI). IEEE, pp 751–755
Liu Z, Feng Y, Zhang Y, Li X (2016) A fusion algorithm for infrared and visible images based on RDU-PCNN and ICA-bases in NSST domain. Infrared Phys Technol 79:183–190
Yang Y, Que Y, Huang SY, Lin P (2017) Technique for multi-focus image fusion based on fuzzy-adaptive pulse-coupled neural network. Signal Image Video Process 11(3):439–446
Zhu S, Wang L, Duan S (2017) Memristive pulse coupled neural network with applications in medical image processing. Neurocomputing 227:149–157
Cheng S, Qiguang M, Pengfei X (2013) A novel algorithm of remote sensing image fusion based on shearlets and PCNN. Neurocomputing 117:47–53
Kong W, Liu J (2013) Technique for image fusion based on nonsubsampled shearlet transform and improved pulse-coupled neural network. Opt Eng 52(1):017001–017001
Baohua Z, Chuanting Z, Yuanyuan L, Jianshuai W, He L (2014) Multi-focus image fusion algorithm based on compound PCNN in surfacelet domain. Opt Int J Light Electron Opt 125(1):296–300
Jin X, Zhou D, Yao S, Nie R, Chuanbo Y, Ding T (2016) Remote sensing image fusion method in cielab color space using nonsubsampled shearlet transform and pulse coupled neural networks. J Appl Remote Sens 10(2):025023–025023
Zhao C, Shao G, Ma L, Zhang X (2014) Image fusion algorithm based on redundant-lifting nswmda and adaptive PCNN. Opt Int J Light Electron Opt 125(20):6247–6255
Liu X, Mei W, Huiqian D (2016) Multimodality medical image fusion algorithm based on gradient minimization smoothing filter and pulse coupled neural network. Biomed Signal Process Control 30:140–148
Wang Z, Wang S, Zhu Y (2017) Multi-focus image fusion based on the improved PCNN and guided filter. Neural Process Lett 45(1):75–94
Wang Z, Wang S, Guo L (2016) Novel multi-focus image fusion based on PCNN and random walks. Neural Comput Appl 1–14
Agrawal D, Singhai J (2010) Multifocus image fusion using modified pulse coupled neural network for improved image quality. IET Image Proc 4(6):443–451
Xinzheng X, Shan D, Wang G, Jiang X (2016) Multimodal medical image fusion using PCNN optimized by the qpso algorithm. Appl Soft Comput 46:588–595
Wang Z, Ma Y (2007) Dual-channel PCNN and its application in the field of image fusion. In: Third international conference on natural computation, 2007. ICNC 2007, vol 1, IEEE, pp 755–759
Chai Y, Li HF, Qu JF (2010) Image fusion scheme using a novel dual-channel PCNN in lifting stationary wavelet domain. Optics Communications 283(19):3591–3602
Wang Z, Ma Y, Jason G (2010) Multi-focus image fusion using PCNN. Pattern Recogn 43(6):2003–2016
Defa H, Shi H, Jiang W (2016) Infrared and visible image fusion using multiscale top-hat transform and modified adaptive dual-channel PCNN. Rev Téc Ing Univ Zulia 39(3):173–180
Shi Y (2016) Image fusion using an improved dual-channel PCNN and block-based random image sampling. Rev Téc Ing Univ Zulia 39(6):421–430
Wang Z, Ma Y (2008) Medical image fusion using M-PCNN. Information Fusion 9(2):176–185
Imamoglu N, Wei Z, Shi H, Yoshida Y, Nergui M, Gonzalez J, Gu D, Chen W, Nonami K, Yu W (2017) Saliency fusion in eigenvector space with multi-channel pulse coupled neural network. arXiv preprint arXiv:1703.00160
Zhao Y, Zhao Q, Hao A (2014) Multimodal medical image fusion using improved multi-channel PCNN. Bio-Med Mater Eng 24(1):221–228
Wang Z, Wang S, Zhu Y, Ma Y (2016) Review of image fusion based on pulse-coupled neural network. Arch Comput Methods Eng 23(4):659–671
Ji L, Yi Z, Shang L, Pu X (2007) Binary fingerprint image thinning using template-based PCNNs. IEEE Trans Syst Man Cybern Part B (Cybern) 37(5):1407–1413
Shang L, Yi Z, Ji L (2007) Binary image thinning using autowaves generated by PCNN. Neural Process Lett 25(1):49–62
Shang L, Yi Z (2007) A class of binary images thinning using two PCNNs. Neurocomputing 70(4):1096–1101
Caulfield JH, Kinser JM (1999) Finding the shortest path in the shortest time using PCNN’s. IEEE Trans Neural Netw 10(3):604–606
Zhang Y, Lenan W (2011) A novel algorithm for apsp problem via a simplified delay pulse coupled neural network. J Comput Inf Syst 7(3):737–744
Sang Y, Lv J, Hong Q, Yi Z (2016) Shortest path computation using pulse-coupled neural networks with restricted autowave. Knowl Based Syst 114:1–11
Kinser JM, Lindblad T (1999) Implementation of pulse-coupled neural networks in a CNAPS environment. IEEE Trans Neural Netw 10(3):584–590
Acknowledgements
This work was jointly supported by the National Natural Science Foundation of China (Grant Nos. 61175012 and 61201421), Natural Science Foundation of Gansu Province (Grant Nos. 145RJZA181 and 1208RJZA265), Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20110211110026), and the Fundamental Research Funds for the Central Universities of China (Grant Nos. lzujbky-2013-k06 and lzujbky-2015-196).
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Yang, Z., Lian, J., Guo, Y. et al. An Overview of PCNN Model’s Development and Its Application in Image Processing. Arch Computat Methods Eng 26, 491–505 (2019). https://doi.org/10.1007/s11831-018-9253-8
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DOI: https://doi.org/10.1007/s11831-018-9253-8