In this paper we propose new filters for the contourlet transform and derive a series of trigonometric filters. Furthermore, we propose a methodology for designing new filters that are obtained from polynomial functions. Thus, we jointly derive different filters for each contourlet decomposition level, and apply them in image denoising. We show that on all the tested images and noise levels, the contourlet transform equipped with the proposed filters clearly outperforms its raised cosine filter-based counterpart in terms of denoising performance. In this sense, when employing polynomial filters, we report gains of up to 0.6dB.
Alecu, A, Munteanu, A, Pizurica, A, Cornelis, J & Schelkens, P 2007, New Improved Filters for the Contourlet Transform with Application in Image Denoising. in International Workshop on Nonlinear Signal and Image Processing, IWNSIP 2007, Bucharest, Romania. pp. 9-14, Finds and Results from the Swedish Cyprus Expedition: A Gender Perspective at the Medelhavsmuseet, Stockholm, Sweden, 21/09/09.
Alecu, A., Munteanu, A., Pizurica, A., Cornelis, J., & Schelkens, P. (2007). New Improved Filters for the Contourlet Transform with Application in Image Denoising. In International Workshop on Nonlinear Signal and Image Processing, IWNSIP 2007, Bucharest, Romania (pp. 9-14)
@inproceedings{3a8748b1e112452081eac3f741f049ad,
title = "New Improved Filters for the Contourlet Transform with Application in Image Denoising",
abstract = "In this paper we propose new filters for the contourlet transform and derive a series of trigonometric filters. Furthermore, we propose a methodology for designing new filters that are obtained from polynomial functions. Thus, we jointly derive different filters for each contourlet decomposition level, and apply them in image denoising. We show that on all the tested images and noise levels, the contourlet transform equipped with the proposed filters clearly outperforms its raised cosine filter-based counterpart in terms of denoising performance. In this sense, when employing polynomial filters, we report gains of up to 0.6dB.",
keywords = "geometric wavelets, contourlets, image denoising",
author = "Alin Alecu and Adrian Munteanu and Alexandra Pizurica and Jan Cornelis and Peter Schelkens",
year = "2007",
month = sep,
day = "10",
language = "English",
pages = "9--14",
booktitle = "International Workshop on Nonlinear Signal and Image Processing, IWNSIP 2007, Bucharest, Romania",
note = "Finds and Results from the Swedish Cyprus Expedition: A Gender Perspective at the Medelhavsmuseet ; Conference date: 21-09-2009 Through 25-09-2009",
}