Joint estimation of signal and noise correlation matrices and its application to inverse filtering.
Akira TanakaMasaaki MiyakoshiPublished in: ICASSP (2009)
Keyphrases
- joint estimation
- correlation matrix
- random noise
- high pass
- bandpass
- additive noise
- nonlinear filters
- white noise
- low signal to noise ratio
- median filter
- removing noise
- high frequency
- filtering method
- low frequency
- wiener filtering
- wide band
- received signal
- signal detection
- spatial filtering
- low snr
- signal to noise ratio
- noise removal
- salt pepper
- noise reduction
- filtering process
- stochastic resonance
- noise detection
- wiener filter
- low pass
- noisy environments
- noise filtering
- multiplicative noise
- noise level
- non stationary
- noise variance
- gaussian noise
- low pass filter
- singular value decomposition
- frequency domain
- linear filters
- noise model
- impulse response
- noisy data
- noisy images
- signal processing
- correlation coefficient
- power spectrum
- autocorrelation function
- additive gaussian noise
- weak signal
- image processing
- correlation function
- noise free
- biomedical signals
- linear minimum mean square error
- direct sequence spread spectrum
- original signal
- gaussian filter
- bilateral filter
- singular values
- missing data
- denoising
- multiscale