Teager-Kaiser energy methods for signal and image analysis: A review

Abstract This paper provides a review of the Teager–Kaiser (TK) energy operator and its extensions for signals and images processing. This class of operators possesses simplicity and good time-resolution and is very efficient in instantaneously estimating AM–FM signals and images. We point out the importance of the concept of energy from the point of view of the generation of the signal. More precisely, we emphasize the importance of analyzing signals from the point of view of the energy of the system needed to produce them. We show how this class of TK energy operators can be used to estimate useful features for signals and images analysis in time, space and frequency domains such as instantaneous frequency, second-order moment frequency, coherence function or spatial envelope and phase. We also show the importance of the higher derivative order of TK energy operator in terms of demodulation for both mono and multi-dimensional signals. Most of the developed tools around TK energy operators deal with real and complex-valued signals and some of them extended to multi-dimensional case. Due to their low complexity and their instantaneous-adapting nature, the class of TK energy operators offers valuable processing tools for time (space), frequency and time–frequency analysis.

[1]  Sanjit K. Mitra,et al.  A GENERALIZATION OF THE TEAGER ALGORITHM , 1998 .

[2]  Boualem Boashash,et al.  Designing high-resolution time-frequency and time-scale distributions for the analysis and classification of non-stationary signals: a tutorial review with a comparison of features performance , 2017, Digit. Signal Process..

[3]  Chenggen Quan,et al.  Determination of phase derivatives from a single fringe pattern using Teager Hilbert Huang transform , 2016 .

[4]  Larry S. Liebovitch,et al.  Predicting optimal drive sweep rates for autoresonance in Duffing-type oscillators: A beat method using Teager–Kaiser instantaneous frequency , 2010 .

[5]  Alfredo Restrepo,et al.  Localized measurement of emergent image frequencies by Gabor wavelets , 1992, IEEE Trans. Inf. Theory.

[6]  Petros Maragos,et al.  On amplitude and frequency demodulation using energy operators , 1993, IEEE Trans. Signal Process..

[7]  Kieran Larkin,et al.  Uniform estimation of orientation using local and nonlocal 2-D energy operators. , 2005, Optics express.

[8]  James F. Kaiser,et al.  Some useful properties of Teager's energy operators , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[9]  Habib Zaidi,et al.  Functional segmentation of dynamic nuclear images by cross-PsiB-energy operator , 2006, Comput. Methods Programs Biomed..

[10]  F Salzenstein,et al.  Local frequency and envelope estimation by Teager-Kaiser energy operators in white-light scanning interferometry. , 2014, Optics express.

[11]  Ping Wei,et al.  Single-channel blind separation of overlapped multicomponents based on energy operator , 2010, Science in China Series F: Information Sciences.

[12]  R. Schafer Homomorphic Systems and Cepstrum Analysis of Speech , 2008 .

[13]  S. Mukhopadhyay,et al.  A new interpretation of nonlinear energy operator and its efficacy in spike detection , 1998, IEEE Transactions on Biomedical Engineering.

[14]  I Kamwa,et al.  Robust Detection and Analysis of Power System Oscillations Using the Teager-Kaiser Energy Operator , 2011, IEEE Transactions on Power Systems.

[15]  Alan C. Bovik,et al.  A Steerable, Multiscale Singularity Index , 2013, IEEE Signal Processing Letters.

[16]  Dennis Gabor,et al.  Theory of communication , 1946 .

[17]  Saeid Sanei,et al.  Spike detection approaches for noisy neuronal data: Assessment and comparison , 2014, Neurocomputing.

[18]  Jean-Philippe Montillet On a Novel Approach to Decompose Finite Energy Functions by Energy Operators and its Application to the General Wave Equation , 2010 .

[19]  Alan C. Bovik,et al.  Multidimensional quasi-eigenfunction approximations and multicomponent AM-FM models , 2000, IEEE Trans. Image Process..

[20]  B. P. Lathi,et al.  Modern Digital and Analog Communication Systems , 1983 .

[21]  Abdel-Ouahab Boudraa Relationships Between $\Psi _{ {\tt B}}$-Energy Operator and Some Time-Frequency Representations , 2010, IEEE Signal Processing Letters.

[22]  Abdel-Ouahab Boudraa,et al.  Higher order Teager-Kaiser operators for image analysis: Part I - A monocomponent image demodulation , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

[23]  Thierry Chonavel,et al.  ΨBΨB-energy operator and cross-power spectral density , 2014, Signal Process..

[24]  T. Hortobágyi,et al.  Teager–Kaiser energy operator signal conditioning improves EMG onset detection , 2010, European Journal of Applied Physiology.

[25]  Stefan Thurnhofer Two-dimensional Teager filters , 2000 .

[26]  Abdel-Ouahab Boudraa,et al.  Multi-dimensional higher order differential operators derived from the Teager-Kaiser energy-tracking function , 2009, Signal Process..

[27]  Abdelkhalek BOUCHIKHI,et al.  Multicomponent AM-FM signals analysis based on EMD-B-splines ESA , 2012, Signal Process..

[28]  T. Irino,et al.  A time-domain, level-dependent auditory filter: The gammachirp , 1997 .

[29]  Les E. Atlas,et al.  Quadratic detectors for energy estimation , 1995, IEEE Trans. Signal Process..

[30]  Petros Maragos,et al.  Energy separation in signal modulations with application to speech analysis , 1993, IEEE Trans. Signal Process..

[31]  Balu Santhanam,et al.  Wideband image demodulation via bi-dimensional multirate frequency transformations. , 2016, Journal of the Optical Society of America. A, Optics, image science, and vision.

[32]  Petros Maragos,et al.  Higher order differential energy operators , 1995, IEEE Signal Processing Letters.

[33]  Athanasios Papoulis,et al.  Probability, Random Variables and Stochastic Processes , 1965 .

[34]  Jean Gotman,et al.  Adaptive segmentation of electroencephalographic data using a nonlinear energy operator , 1999, ISCAS'99. Proceedings of the 1999 IEEE International Symposium on Circuits and Systems VLSI (Cat. No.99CH36349).

[35]  Boualem Boashash,et al.  Time-frequency features for pattern recognition using high-resolution TFDs: A tutorial review , 2015, Digit. Signal Process..

[36]  Mark A. Poletti Instantaneous frequency and conditional moments in the time-frequency plane , 1991, IEEE Trans. Signal Process..

[37]  Joseph P. Havlicek,et al.  AM-FM Image Models: Fundamental Techniques and Emerging Trends , 2005 .

[38]  Jun Ni,et al.  Chatter Detection in Machining Using Nonlinear Energy Operator , 2010 .

[39]  John H. L. Hansen,et al.  Howling Detection in Hearing Aids Based on Generalized Teager–Kaiser Operator , 2015, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[40]  Petros Maragos,et al.  Image demodulation using multidimensional energy separation , 1995 .

[41]  Richard H. Lyon,et al.  Estimation of Structural Response to Reverberant Sound Fields; Experimental Results , 1961 .

[42]  Petros Maragos,et al.  Multiband Modulation Energy Tracking for Noisy Speech Detection , 2006, IEEE Transactions on Audio, Speech, and Language Processing.

[43]  Yi Qin,et al.  Multicomponent AM–FM demodulation based on energy separation and adaptive filtering , 2013 .

[44]  Rajib Sharma,et al.  Empirical Mode Decomposition for adaptive AM-FM analysis of Speech: A Review , 2017, Speech Commun..

[45]  Thierry Chonavel,et al.  Analysis of multicomponent LFM signals by Teager Huang-Hough transform , 2014, IEEE Transactions on Aerospace and Electronic Systems.

[46]  Abdel-Ouahab Boudraa,et al.  Image contrast enhancement based on 2D Teager-Kaiser operator , 2008, 2008 15th IEEE International Conference on Image Processing.

[47]  Thierry Chonavel,et al.  A new class of multi-dimensional Teager-Kaiser and higher order operators based on directional derivatives , 2013, Multidimens. Syst. Signal Process..

[48]  Abdel-Ouahab Boudraa,et al.  Link between cross-Wigner distribution and cross-Teager energy operator , 2004 .

[49]  John M. O'Toole,et al.  Assessing instantaneous energy in the EEG: A non-negative, frequency-weighted energy operator , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[50]  Alfredo Restrepo,et al.  Root and pre-constant signals of the 1D Teager-Kaiser operator , 2011, Signal Image Video Process..

[51]  A. Enis Çetin,et al.  Teager energy based feature parameters for speech recognition in car noise , 1999, IEEE Signal Processing Letters.

[52]  P. Frank Pai,et al.  Instantaneous frequency of an arbitrary signal , 2010 .

[53]  Douglas OʼShaughnessy Formant Estimation and Tracking , 2008 .

[54]  Abdel-Ouahab Boudraa,et al.  Speech enhancement using empirical mode decomposition and the Teager-Kaiser energy operator. , 2014, The Journal of the Acoustical Society of America.

[55]  Hae-Jeong Park,et al.  Automated detection and elimination of periodic ECG artifacts in EEG using the energy interval histogram method , 2002, IEEE Transactions on Biomedical Engineering.

[56]  Mark L. Fowler,et al.  Phase-Based Frequency Estimation: A Review , 2002, Digit. Signal Process..

[57]  Petros Maragos,et al.  On the improvement of modulation features using multi-microphone energy tracking for robust distant speech recognition , 2017, 2017 25th European Signal Processing Conference (EUSIPCO).

[58]  Wen-Liang Hwang,et al.  Multicomponent AM-FM signal separation and demodulation with null space pursuit , 2013, Signal Image Video Process..

[59]  Petros Maragos,et al.  Conditions for positivity of an energy operator , 1994, IEEE Trans. Signal Process..

[60]  Boualem Boashash,et al.  Time-Frequency Signal Analysis and Processing: A Comprehensive Reference , 2015 .

[61]  Marc Thomas,et al.  A Frequency-Weighted Energy Operator and complementary ensemble empirical mode decomposition for bearing fault detection , 2017 .

[62]  Antoine Coutrot,et al.  Video viewing: do auditory salient events capture visual attention? , 2013, annals of telecommunications - annales des télécommunications.

[63]  Sanjit K. Mitra,et al.  Nonlinear unsharp masking methods for image contrast enhancement , 1996, J. Electronic Imaging.

[64]  Petros Maragos,et al.  Multimodal Saliency and Fusion for Movie Summarization Based on Aural, Visual, and Textual Attention , 2013, IEEE Transactions on Multimedia.

[65]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[66]  F. Salzenstein,et al.  IF estimation using empirical mode decomposition and nonlinear Teager energy operator , 2004, First International Symposium on Control, Communications and Signal Processing, 2004..

[67]  Abdel-Ouahab Boudraa,et al.  A joint 2D AM–FM estimation based on higher order Teager–Kaiser energy operators , 2011, Signal Image Video Process..

[68]  Salah Bourennane,et al.  Time-Delay Estimation Using Cross-ΨB-Energy Operator , 2007 .

[69]  Weidong Xiang,et al.  On the nonlinear Teager-Kaiser operator for energy detection based impulse radio UWB receivers , 2012, 2012 IEEE Global Communications Conference (GLOBECOM).

[70]  Douglas A. Reynolds,et al.  Fine structure features for speaker identification , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[71]  Yu-Ling He,et al.  Time-Frequency Analysis Based on Improved Variational Mode Decomposition and Teager Energy Operator for Rotor System Fault Diagnosis , 2016 .

[72]  Abdel-Ouahab Boudraa,et al.  Nonstationary signals analysis by Teager-Huang Transform (THT) , 2006, 2006 14th European Signal Processing Conference.

[73]  Michael Felsberg,et al.  GET: The Connection Between Monogenic Scale-Space and Gaussian Derivatives , 2005, Scale-Space.

[74]  Petros Maragos,et al.  On separating amplitude from frequency modulations using energy operators , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[75]  Abdel-Ouahab Boudraa,et al.  Higher order Teager-Kaiser operators for image analysis: PART II - a multicomponent image demodulation , 2009, ICIP.

[76]  Iasonas Kokkinos,et al.  Texture Analysis and Segmentation Using Modulation Features, Generative Models, and Weighted Curve Evolution , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[77]  J. F. Kaiser,et al.  On a simple algorithm to calculate the 'energy' of a signal , 1990, International Conference on Acoustics, Speech, and Signal Processing.

[78]  Pradip Sircar,et al.  Analysis of multicomponent AM-FM signals using FB-DESA method , 2010, Digit. Signal Process..

[79]  Abdel-Ouahab Boudraa,et al.  An Energy-Based Similarity Measure for Time Series , 2008, EURASIP J. Adv. Signal Process..

[80]  Abdel-Ouahab Boudraa,et al.  Mesure de similarité de signaux par opérateur d'énergie croisée , 2017 .

[81]  Sanjit K. Mitra,et al.  A new class of nonlinear filters for image enhancement , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.

[82]  A. Savitzky,et al.  Smoothing and Differentiation of Data by Simplified Least Squares Procedures. , 1964 .

[83]  I. Toshio An optimal auditory filter , 1995, Proceedings of 1995 Workshop on Applications of Signal Processing to Audio and Accoustics.

[84]  Jong-Ho Choi,et al.  Neural action potential detector using multi-resolution TEO , 2002 .

[85]  J. F. Kaiser,et al.  Instantaneous non-linear operators for tracking multicomponent signal parameters , 1992, [1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing.

[86]  Jin Jiang,et al.  Time-frequency feature representation using energy concentration: An overview of recent advances , 2009, Digit. Signal Process..

[87]  Balu Santhanam On a matrix framework for the Teager-Kaiser energy operator , 2013, 2013 IEEE Digital Signal Processing and Signal Processing Education Meeting (DSP/SPE).

[88]  J. C. Cexus,et al.  Teager-Huang Analysis Applied to Sonar Target Recognition , 2007 .

[89]  Abdel-Ouahab Boudraa,et al.  Teager-Kaiser Energy and Higher-Order Operators in White-Light Interference Microscopy for Surface Shape Measurement , 2005, EURASIP J. Adv. Signal Process..

[90]  Yannis Stylianou,et al.  Detection of sperm whale clicks based on the Teager–Kaiser energy operator , 2006 .

[91]  P. Maragos,et al.  Speech formant frequency and bandwidth tracking using multiband energy demodulation , 1996 .

[92]  Igor Djurovic,et al.  Review of the quasi-maximum likelihood estimator for polynomial phase signals , 2018, Digit. Signal Process..

[93]  Thierry Chonavel,et al.  Some useful properties of cross-ΨB-energy operator , 2009 .

[94]  Abdel-Ouahab Boudraa,et al.  Generalized higher-order nonlinear energy operators. , 2007, Journal of the Optical Society of America. A, Optics, image science, and vision.

[95]  Petros Maragos,et al.  Robust AM-FM features for speech recognition , 2005, IEEE Signal Processing Letters.

[96]  Khaled H. Hamed,et al.  Time-frequency analysis , 2003 .

[97]  Petros Maragos,et al.  A comparison of the energy operator and the Hilbert transform approach to signal and speech demodulation , 1994, Signal Process..

[98]  Eric Fogarassy,et al.  Large area, high resolution analysis of surface roughness of semiconductors using interference microscopy , 2002 .

[99]  Meryem Jabloun A new generalization of the discrete Teager-Kaiser energy operator - application to biomedical signals , 2017, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[100]  Karim Abed-Meraim,et al.  Interaction measure of AM-FM signals by cross-Psi_B-energy operator , 2005 .

[101]  Petros Maragos,et al.  AM-FM energy detection and separation in noise using multiband energy operators , 1993, IEEE Trans. Signal Process..

[102]  Matthieu Hébert,et al.  Text-Dependent Speaker Recognition , 2008 .

[103]  H. Teager Some observations on oral air flow during phonation , 1980 .

[104]  Norden E. Huang,et al.  On Instantaneous Frequency , 2009, Adv. Data Sci. Adapt. Anal..

[105]  Petros Maragos,et al.  Continuous energy demodulation methods and application to speech analysis , 2006, Speech Commun..

[106]  David Vakman,et al.  On the analytic signal, the Teager-Kaiser energy algorithm, and other methods for defining amplitude and frequency , 1996, IEEE Trans. Signal Process..

[107]  M. Moshinsky,et al.  The harmonic oscillator in modern physics , 1996 .

[108]  K. Abed-Meraim,et al.  Cross Psi(B)-energy operator-based signal detection. , 2008, The Journal of the Acoustical Society of America.

[109]  John H. L. Hansen,et al.  Teager–Kaiser Energy Operators for Overlapped Speech Detection , 2017, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[110]  Petros Maragos,et al.  A Comparison of the Squared Energy and Teager-Kaiser Operators for Short-Term Energy Estimation in Additive Noise , 2009, IEEE Transactions on Signal Processing.

[111]  J. Daugman Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[112]  James H. McClellan,et al.  Instantaneous frequency estimation using linear prediction with comparisons to the DESAs , 1996, IEEE Signal Processing Letters.

[113]  Alfred Mertins,et al.  Analysis and design of gammatone signal models. , 2009, The Journal of the Acoustical Society of America.

[114]  David Zhang,et al.  GMAT: Glottal closure instants detection based on the Multiresolution Absolute Teager-Kaiser energy operator , 2017, Digit. Signal Process..

[115]  Abdel-Ouahab Boudraa,et al.  Two-dimensional continuous higher-order energy operators , 2005 .

[116]  Hong Yan,et al.  Clustering of temporal gene expression data by regularized spline regression and an energy based similarity measure , 2010, Pattern Recognit..

[117]  Petros Maragos,et al.  An improved energy demodulation algorithm using splines , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[118]  Petros Maragos,et al.  Energy demodulation of two-component AM-FM signals with application to speaker separation , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[119]  Srdjan Stankovic,et al.  Instantaneous frequency in time-frequency analysis: Enhanced concepts and performance of estimation algorithms , 2014, Digit. Signal Process..

[120]  Stan Davis,et al.  Comparison of Parametric Representations for Monosyllabic Word Recognition in Continuously Spoken Se , 1980 .

[121]  Abdel-Ouahab Boudraa,et al.  Instantaneous frequency estimation of FM signals by Ψ B -energy operator , 2011 .

[122]  Jaakko Astola,et al.  Teager energy and the ambiguity function , 1999, IEEE Trans. Signal Process..

[123]  Petros Maragos,et al.  Auditory Teager energy cepstrum coefficients for robust speech recognition , 2005, INTERSPEECH.

[124]  Harish Garg,et al.  Nonstationary-epileptic-spike detection algorithm in EEG signal using SNEO , 2013 .

[125]  Cyril Ray,et al.  Amplitude-based dominant component analysis for underwater mines extraction in side scans sonar , 2016, OCEANS 2016 - Shanghai.

[126]  T. Moon,et al.  Mathematical Methods and Algorithms for Signal Processing , 1999 .

[127]  Igor Djurovic,et al.  Cubic phase function: A simple solution to polynomial phase signal analysis , 2017, Signal Process..

[128]  Abdel-Ouahab Boudraa,et al.  Image source detection for geoacoustic inversion by the Teager-Kaiser energy operator. , 2014, The Journal of the Acoustical Society of America.

[129]  Patrick Flandrin,et al.  Improving the readability of time-frequency and time-scale representations by the reassignment method , 1995, IEEE Trans. Signal Process..

[130]  Petros Maragos,et al.  Speech nonlinearities, modulations, and energy operators , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.