@inproceedings{f106b9b4a59f419eb8edb39f27ee45ea,
title = "Benefits of consistency in image denoising with steerable wavelets",
abstract = "The steerable wavelet transform is a redundant image representation with the remarkable property that its basis functions can be adaptively rotated to a desired orientation. This makes the transform well-suited to the design of wavelet-based algorithms applicable to images with a high amount of directional features. However, arbitrary modification of the wavelet-domain coefficients may violate consistency constraints because a legitimate representation must be redundant. In this paper, by honoring the redundancy of the coefficients, we demonstrate that it is possible to improve the performance of regularized least-squares problems in the steerable wavelet domain. We illustrate that our consistent method significantly improves upon the performance of conventional denoising with steerable wavelets.",
keywords = "Image denoising, sparse estimation, steerable wavelet transform, wavelet regularization",
author = "Bugra Tekin and Kamilov, \{Ulugbek S.\} and Emrah Bostan and Michael Unser",
year = "2013",
month = oct,
day = "18",
doi = "10.1109/ICASSP.2013.6637872",
language = "English",
isbn = "9781479903566",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
pages = "1355--1358",
booktitle = "2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings",
note = "2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 ; Conference date: 26-05-2013 Through 31-05-2013",
}