2 February 2012 A new denoising method in high-dimensional PCA-space
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Abstract
Kernel-design based method such as Bilateral filter (BIL), non-local means (NLM) filter is known as one of the most attractive approaches for denoising. We propose in this paper a new noise filtering method inspired by BIL, NLM filters and principal component analysis (PCA). The main idea here is to perform the BIL in a multidimensional PCA-space using an anisotropic kernel. The filtered multidimensional signal is then transformed back onto the image spatial domain to yield the desired enhanced image. In this work, it is demonstrated that the proposed method is a generalization of kernel-design based methods. The obtained results are highly promising.
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Quoc Bao Do, Azeddine Beghdadi, Marie Luong, "A new denoising method in high-dimensional PCA-space", Proc. SPIE 8295, Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II, 82950R (2 February 2012); doi: 10.1117/12.909011; https://doi.org/10.1117/12.909011
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KEYWORDS
Image filtering

Principal component analysis

Denoising

Gaussian filters

Image quality

Image restoration

Image processing

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