DocumentCode :
2545191
Title :
A stochastic diffusion approach to signal denoising
Author :
Krim, Hamid ; Bao, Yufang
Author_Institution :
Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA
fYear :
2000
fDate :
2000
Firstpage :
236
Lastpage :
239
Abstract :
We present a stochastic formulation of a linear diffusion equation (or heat equation), and in light of the potential applications ranging from signal denoising to image enhancement/segmentation of its nonlinear extensions, we propose a more general nonlinear stochastic diffusion. The constructed stochastic framework, in contrast to traditional deterministic approaches, unveils the sources of of existing limitations and allows us to further significantly improve the performance by addressing the key problem. Substantiating examples are provided
Keywords :
AWGN; diffusion; filtering theory; image enhancement; image segmentation; nonlinear filters; partial differential equations; AWGN; PDE; SNR; additive white Gaussian noise; heat equation; image enhancement; image segmentation; linear diffusion equation; nonlinear filter; nonlinear stochastic diffusion; partial differential equation; signal denoising; staircase function; Kernel; Noise reduction; Nonlinear equations; Signal analysis; Signal denoising; Space heating; Stochastic processes; Stochastic resonance; Wavelet analysis; Working environment noise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Sensor Array and Multichannel Signal Processing Workshop. 2000. Proceedings of the 2000 IEEE
Conference_Location :
Cambridge, MA
Print_ISBN :
0-7803-6339-6
Type :
conf
DOI :
10.1109/SAM.2000.878005
Filename :
878005
Link To Document :
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