An Image Denoising Method with Enhancement of the Directional Features Based on Wavelet and SVD Transforms

Min Wang, Zhen Li, Xiangjun Duan and Wei Li

Mathematical Problems in Engineering, 2015, vol. 2015, 1-9

Abstract:

This paper proposes an image denoising method, using the wavelet transform and the singular value decomposition (SVD), with the enhancement of the directional features. First, use the single-level discrete 2D wavelet transform to decompose the noised image into the low-frequency image part and the high-frequency parts (the horizontal, vertical, and diagonal parts), with the edge extracted and retained to avoid edge loss. Then, use the SVD to filter the noise of the high-frequency parts with image rotations and the enhancement of the directional features: to filter the diagonal part, one needs first to rotate it 45 degrees and rotate it back after filtering. Finally, reconstruct the image from the low-frequency part and the filtered high-frequency parts by the inverse wavelet transform to get the final denoising image. Experiments show the effectiveness of this method, compared with relevant methods.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:469350

DOI: 10.1155/2015/469350

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