This paper proposes a novel approach for image and signal denoising that does not need any classical regularization. It subtracts a sorted realization of noise to the sorted noisy signal. The similarity between the noise that corrupted the signal and the selected noise realization allows us to denoise monotonic signals. The Minimum Description Length (MDL) is then adopted to get a piecewise monotonic representation of the original signal. Experimental results show that the proposed approach outperforms most of the classical denoising approaches, even though it is based on very simple operations. © 2013 IEEE.
Signal and image denoising without regularization / Bruni, Vittoria; Vitulano, D.. - ELETTRONICO. - (2013), pp. 539-542. (Intervento presentato al convegno 2013 20th IEEE International Conference on Image Processing, ICIP 2013 tenutosi a Melbourne, VIC nel 15 September 2013 through 18 September 2013) [10.1109/icip.2013.6738111].
Signal and image denoising without regularization
BRUNI, VITTORIA;D. Vitulano
2013
Abstract
This paper proposes a novel approach for image and signal denoising that does not need any classical regularization. It subtracts a sorted realization of noise to the sorted noisy signal. The similarity between the noise that corrupted the signal and the selected noise realization allows us to denoise monotonic signals. The Minimum Description Length (MDL) is then adopted to get a piecewise monotonic representation of the original signal. Experimental results show that the proposed approach outperforms most of the classical denoising approaches, even though it is based on very simple operations. © 2013 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
