Memristor bridge-based low pass filter for image processing
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摘要
This paper highlights the memristor bridge-based lowpass filter(LPF) and improved image processing algorithms along with a novel adaptive Gaussian filter for denoising image and a new Gaussian pyramid for scale invariant feature transform(SIFT). First, a novel kind of LPF based on the memristor bridge is designed, whose cut-off frequency and other traits are demonstrated to change with different time and memristance. In light of the changeable parameter of the memristor bridge-based LPF, a new adaptive Gaussian filter and an improved SIFT algorithm are presented. Finally, experiment results show that the peak signalto-noise ratio(PSNR) of our denoising is bettered more than 2.77 dB compared to the corresponding of the traditional Gaussian filter, and our improved SIFT performances including the number of matched feature points and the percent of correct matches are higher than the traditional SIFT, which verifies feasibility and effectiveness of our algorithm.
This paper highlights the memristor bridge-based lowpass filter(LPF) and improved image processing algorithms along with a novel adaptive Gaussian filter for denoising image and a new Gaussian pyramid for scale invariant feature transform(SIFT). First, a novel kind of LPF based on the memristor bridge is designed, whose cut-off frequency and other traits are demonstrated to change with different time and memristance. In light of the changeable parameter of the memristor bridge-based LPF, a new adaptive Gaussian filter and an improved SIFT algorithm are presented. Finally, experiment results show that the peak signalto-noise ratio(PSNR) of our denoising is bettered more than 2.77 dB compared to the corresponding of the traditional Gaussian filter, and our improved SIFT performances including the number of matched feature points and the percent of correct matches are higher than the traditional SIFT, which verifies feasibility and effectiveness of our algorithm.
This paper highlights the memristor bridge-based lowpass filter(LPF) and improved image processing algorithms along with a novel adaptive Gaussian filter for denoising image and a new Gaussian pyramid for scale invariant feature transform(SIFT). First, a novel kind of LPF based on the memristor bridge is designed, whose cut-off frequency and other traits are demonstrated to change with different time and memristance. In light of the changeable parameter of the memristor bridge-based LPF, a new adaptive Gaussian filter and an improved SIFT algorithm are presented. Finally, experiment results show that the peak signalto-noise ratio(PSNR) of our denoising is bettered more than 2.77 dB compared to the corresponding of the traditional Gaussian filter, and our improved SIFT performances including the number of matched feature points and the percent of correct matches are higher than the traditional SIFT, which verifies feasibility and effectiveness of our algorithm.
引文
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[3]BAKER K D,SULLIVAN G D.Multiple bandpass filters in image processing.IEE Proceedings E-Computers and Digital Techniques,1980,127(5):173-184.
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[5]ZHANG Z,WONG K H.A computer vision based sea search method using Kalman filter and CAMSHIFT.Proc.of the International Conference on Technological Advances in Electrical,Electronics and Computer Engineering,2013:188-193.
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[9]OPPENHEIM A,SCHAFER R,STOCKHAM T.Nonlinear filtering of multiplied and convolved signals.IEEE Trans.on Audio and Electro-Acoustics,1968,16(3):437-466.
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[12]STRUKOV D B,SNIDER G S,STEWART D R,et al.The missing memristor found.Nature,2008,453(7191):80.
[13]BORGHETTI J,SNIDER G S,KUEKES P J,et al.‘Memristive’s witches enable‘stateful’logic operations via material implication.Nature,2010,464(7290):873.
[14]ITOH M,CHUA L.Memristor cellular automata and memristor discrete-time cellular neural networks.International Journal of Bifurcation and Chaos,2009,19(11):3605-3656.
[15]JO S H,CHANG T,EBONG I,et al.Nano-scale memristor device as synapse in neuromorphic systems.Nano Letters,2010,10(4):1297-1301.
[16]XIA Q,ROBINETT W,CUMBIE M W,et al.MemristorCMOS hybrid integrated circuits for reconfigurable logic.Nano Letters,2009,9(10):3640-3645.
[17]KIM H,SAH M P,YANG C,et al.Memristorbridge synapses.Proceedings of the IEEE,2012,100(6):2061-2070.
[18]ADHIKARI S P,YANG C,KIM H,et al.Memristor bridge synapse-based neural network and its learning.IEEE Trans.on Neural Networks and Learning Systems,2012,23(9):1426-1435.
[19]WANG W,YU Q,XU C,et al.Study of filter characteristics based on PWL memristor.Proc.of the International Conference on Communications,Circuits and Systems,2009:969-973.
[20]CHEW Z J,LI L.Printed circuit board based memristor in adaptive low pass filter.Electronics Letters,2012,48(25):1610-1611.
[21]YENER S C,MUTLU R,KUNTMAN H.A new memristorbased high-pass filter/amplifier:its analytical and dynamical models.Proc.of the 24th IEEE International Conference on Radio Elektronika,2014:1-4.
[22]BAO B,WANG N,XU Q,et al.A simple third-order memristive band pass filter chaotic circuit.IEEE Trans.on Circuits Systems II:Express Briefs,2016,64(8):977-981.
[23]HONG Y,LIAN Y.A memristor-based continuous-time digital FIR filter for biomedical signal processing.IEEE Trans.on Circuits and Systems I:Regular Papers,2015,62(5):1392-1401.
[24]LI Y,YANG C,YU Y,et al.Research on low pass filter based on memristor and memcapacitor.Proc.of the 36th IEEE Chinese Control Conference,2017:5110-5113.
[25]CHAN S H,ZICKLER T,LU Y M.Understanding symmetric smoothing filters:a Gaussian mixture model perspective.IEEE Trans.on Image Processing,2017,26(11):5107-5121.
[26]SOZEN H,CAM U.First-order memristor-capacitor filter circuits employing HP memristor.Journal of Circuits,Systems,and Computers,2014,23(8):1450116.
[27]WANG M,ZHENG S,LI X,et al.A new image denoising method based on Gaussian filter.Proc.of the IEEE International Conference on Information Science,Electronics and Electrical Engineering,2014:163-167.
[28]BELYAEV Y,SEIDEL H.Mesh smoothing by adaptive and anisotropic Gaussian filter applied to mesh normal.Proc.of the Vision,Modeling,and Visualization,2002:203-210.
[29]GOMEZ G.Local smoothness in terms of variance:the adaptive Gaussian filter.Proc.of the British Machine Vision Conference,2000:1-10.
[30]LOWE D G.Object recognition from local scale-invariant features.Proc.of the 7th IEEE International Conference on Computer Vision,1999:1150-1157.
[31]LOWE D G.Distinctive image features from scale-invariant keypoints.International Journal of Computer Vision,2004,60(2):91-110.
[2]PLATANIOTIS K N,ANDROUTSOS D,VENET-SANOPOULOS A N.An adaptive multichannel filter for colour image processing.Canadian Journal of Electrical and Computer Engineering,1996,21(4):149-152.
[3]BAKER K D,SULLIVAN G D.Multiple bandpass filters in image processing.IEE Proceedings E-Computers and Digital Techniques,1980,127(5):173-184.
[4]LUCIANO P,SOTIROPOULOU C L,GKAITATZIS S,et al.A hardware implementation of a brain inspired filter for image processing.IEEE Trans.on Nuclear Science,2017,64(6):1374-1381.
[5]ZHANG Z,WONG K H.A computer vision based sea search method using Kalman filter and CAMSHIFT.Proc.of the International Conference on Technological Advances in Electrical,Electronics and Computer Engineering,2013:188-193.
[6]STEINER I,JULLIEN G A.A fault-tolerant complex FIR filter for So C communication technologies.Proc.of the IEEERecord of the 41st Asilomar Conference on Signals,Systems and Computers,2007:2009-2013.
[7]NIU X,WU X,XIE P,et al.A time-frequency analysis of event-related desynchronization/synchronization based on Gabor filter.Proc.of the 11th World Congress on IEEE Intelligent Control and Automation,2014:5179-5184.
[8]HERENCSAR N,VRBA K,KOTON J,et al.The conception of differential-input buffered and trans-conductance amplifier(DBTA)and its application.IEICE Electronics Express,2009,6(6):329-334.
[9]OPPENHEIM A,SCHAFER R,STOCKHAM T.Nonlinear filtering of multiplied and convolved signals.IEEE Trans.on Audio and Electro-Acoustics,1968,16(3):437-466.
[10]MOTWANI M C,GADIYA M C,MOTWANI R C,et al.Survey of image denoising techniques.Proc.of the Global Signal Processing Conference,2004:27-30.
[11]CHUA L.Memristor-the missing circuit element.IEEE Trans.on Circuit Theory,1971,18(5):507-519.
[12]STRUKOV D B,SNIDER G S,STEWART D R,et al.The missing memristor found.Nature,2008,453(7191):80.
[13]BORGHETTI J,SNIDER G S,KUEKES P J,et al.‘Memristive’s witches enable‘stateful’logic operations via material implication.Nature,2010,464(7290):873.
[14]ITOH M,CHUA L.Memristor cellular automata and memristor discrete-time cellular neural networks.International Journal of Bifurcation and Chaos,2009,19(11):3605-3656.
[15]JO S H,CHANG T,EBONG I,et al.Nano-scale memristor device as synapse in neuromorphic systems.Nano Letters,2010,10(4):1297-1301.
[16]XIA Q,ROBINETT W,CUMBIE M W,et al.MemristorCMOS hybrid integrated circuits for reconfigurable logic.Nano Letters,2009,9(10):3640-3645.
[17]KIM H,SAH M P,YANG C,et al.Memristorbridge synapses.Proceedings of the IEEE,2012,100(6):2061-2070.
[18]ADHIKARI S P,YANG C,KIM H,et al.Memristor bridge synapse-based neural network and its learning.IEEE Trans.on Neural Networks and Learning Systems,2012,23(9):1426-1435.
[19]WANG W,YU Q,XU C,et al.Study of filter characteristics based on PWL memristor.Proc.of the International Conference on Communications,Circuits and Systems,2009:969-973.
[20]CHEW Z J,LI L.Printed circuit board based memristor in adaptive low pass filter.Electronics Letters,2012,48(25):1610-1611.
[21]YENER S C,MUTLU R,KUNTMAN H.A new memristorbased high-pass filter/amplifier:its analytical and dynamical models.Proc.of the 24th IEEE International Conference on Radio Elektronika,2014:1-4.
[22]BAO B,WANG N,XU Q,et al.A simple third-order memristive band pass filter chaotic circuit.IEEE Trans.on Circuits Systems II:Express Briefs,2016,64(8):977-981.
[23]HONG Y,LIAN Y.A memristor-based continuous-time digital FIR filter for biomedical signal processing.IEEE Trans.on Circuits and Systems I:Regular Papers,2015,62(5):1392-1401.
[24]LI Y,YANG C,YU Y,et al.Research on low pass filter based on memristor and memcapacitor.Proc.of the 36th IEEE Chinese Control Conference,2017:5110-5113.
[25]CHAN S H,ZICKLER T,LU Y M.Understanding symmetric smoothing filters:a Gaussian mixture model perspective.IEEE Trans.on Image Processing,2017,26(11):5107-5121.
[26]SOZEN H,CAM U.First-order memristor-capacitor filter circuits employing HP memristor.Journal of Circuits,Systems,and Computers,2014,23(8):1450116.
[27]WANG M,ZHENG S,LI X,et al.A new image denoising method based on Gaussian filter.Proc.of the IEEE International Conference on Information Science,Electronics and Electrical Engineering,2014:163-167.
[28]BELYAEV Y,SEIDEL H.Mesh smoothing by adaptive and anisotropic Gaussian filter applied to mesh normal.Proc.of the Vision,Modeling,and Visualization,2002:203-210.
[29]GOMEZ G.Local smoothness in terms of variance:the adaptive Gaussian filter.Proc.of the British Machine Vision Conference,2000:1-10.
[30]LOWE D G.Object recognition from local scale-invariant features.Proc.of the 7th IEEE International Conference on Computer Vision,1999:1150-1157.
[31]LOWE D G.Distinctive image features from scale-invariant keypoints.International Journal of Computer Vision,2004,60(2):91-110.
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