TY - GEN
T1 - Multicomponent Signal Decomposition Using Morphological Operations
AU - Zhuang, Huiping
AU - Oh, Beom Seok
AU - Lin, Dongyun
AU - Toh, Kar Ann
AU - Lin, Zhiping
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - In this paper, we consider the component decomposition (CD) problem in a non-stationary multicomponent signal (MCS). A new technique by manipulation of morphological operations is developed to solve the CD problem. The spectrogram of the MCS is first converted into a binary image. Then, a modified opening operator is adopted to isolate the regions characterizing the individual components while suppressing the noise. The modified opening operation also compensates the energy loss caused in the binarization step. Subsequently, the regions containing the individual components are extracted using a connected-component labeling algorithm. Finally, the time-domain signals for the extracted components are reconstructed using inverse short time Fourier transform. Numerical results show that the proposed method works well for both synthetic and real data and performs better than a competing state-of-the-art method.
AB - In this paper, we consider the component decomposition (CD) problem in a non-stationary multicomponent signal (MCS). A new technique by manipulation of morphological operations is developed to solve the CD problem. The spectrogram of the MCS is first converted into a binary image. Then, a modified opening operator is adopted to isolate the regions characterizing the individual components while suppressing the noise. The modified opening operation also compensates the energy loss caused in the binarization step. Subsequently, the regions containing the individual components are extracted using a connected-component labeling algorithm. Finally, the time-domain signals for the extracted components are reconstructed using inverse short time Fourier transform. Numerical results show that the proposed method works well for both synthetic and real data and performs better than a competing state-of-the-art method.
KW - binary image
KW - connect-component labeling
KW - morphological operation
KW - Multicomponent signal decomposition
UR - http://www.scopus.com/inward/record.url?scp=85062769284&partnerID=8YFLogxK
U2 - 10.1109/ICDSP.2018.8631863
DO - 10.1109/ICDSP.2018.8631863
M3 - Conference contribution
AN - SCOPUS:85062769284
T3 - International Conference on Digital Signal Processing, DSP
BT - 2018 IEEE 23rd International Conference on Digital Signal Processing, DSP 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd IEEE International Conference on Digital Signal Processing, DSP 2018
Y2 - 19 November 2018 through 21 November 2018
ER -