Image denoising using bilateral filter in high dimensional PCA-space

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Abstract

This paper proposes a new noise filtering method inspired by Bilateral filter (BF), non-local means (NLM) filter and principal component analysis (PCA). The main idea here is to perform the BF 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. The proposed method is compared to the state-of-art. The obtained results are highly promising. © 2011 Springer-Verlag.

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APA

Do, Q. B., Beghdadi, A., & Luong, M. (2011). Image denoising using bilateral filter in high dimensional PCA-space. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6855 LNCS, pp. 372–379). https://doi.org/10.1007/978-3-642-23678-5_44

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