Abstract
The denoising of a natural image corrupted by Gaussian white noise is a classical problem in image processing. In this paper, a new image denoising method is proposed by using the contourlet transform. The thresholding process employs a small neighbourhood for the current contourlet coefficient to be thresholded. This is because the contourlet coefficients are correlated, and large contourlet coefficients will normally have large coefficients at its neighbour locations. Experiments show that the proposed method is better than the standard contourlet denoising and the wavelet denoising.
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Chen, G., Zhu, WP. (2008). Image Denoising Using Neighbouring Contourlet Coefficients. In: Sun, F., Zhang, J., Tan, Y., Cao, J., Yu, W. (eds) Advances in Neural Networks - ISNN 2008. ISNN 2008. Lecture Notes in Computer Science, vol 5264. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87734-9_44
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DOI: https://doi.org/10.1007/978-3-540-87734-9_44
Publisher Name: Springer, Berlin, Heidelberg
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