SURE-Based Wavelet Thresholding Integrating Inter-Scale Dependencies

We propose here a new pointwise wavelet thresholding function that incorporates inter-scale dependencies. This non-linear function depends on a set of four linear parameters per subband which are set by minimizing Stein's unbiased MSE estimate (SURE). Our approach assumes additive Gaussian white noise. In order for the inter-scale dependencies to be faithfully taken into account, we also develop a rigorous feature alignment processing, that is adapted to arbitrary wavelet filters (e.g. non-symmetric filters). Finally, we demonstrate the efficiency of our denoising approach in simulations over a wide range of noise levels for a representative set of standard images.


Published in:
Proceedings of the 2006 IEEE International Conference on Image Processing (ICIP'06), Atlanta GA, USA, 1457–1460
Year:
2006
Publisher:
IEEE
Laboratories:




 Record created 2015-09-18, last modified 2018-12-03

External links:
Download fulltextURL
Download fulltextURL
Download fulltextURL
Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)