Adaptive image denoising and edge enhancement in scale-space using the wavelet transform

Authors:
Cláudio Rosito Jung;Jacob Scharcanski
Affiliations:
UNISINOS--Universidade do Vale do Rio dos Sinos, Centro de Ciencias Exatas e Tecnológicas--C6/6 Av. UNISINOS 950, São Leopoldo RS 93022-000, Brazil;UFRGS--Universidade Federal do Rio Grande do Sul Instituto de Informática, Av. Bento Gonçalves 9500, Porto Alegre, RS 91501-970, Brazil
Venue:
Pattern Recognition Letters - Special issue: Sibgrapi 2001
Year:
2003

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Abstract

This paper proposes a new method for image denoising with edge preservation and enhancement, based on image multi-resolution decomposition by a redundant wavelet transform. At each resolution, the coefficients associated with noise and the coefficients associated with edges are modeled by Gaussians, and a shrinkage function is assembled. The shrinkage functions are combined in consecutive resolutions, and geometric constraints are applied to preserve edges that are not isolated. Within the proposed framework, edge related coefficients may be enhanced and denoised simultaneously. Finally, the inverse wavelet transform is applied to the modified coefficients. This method is adaptive, and performs well for images contaminated by natural and artificial noise.