Denoising of multi-modal images with PCA self-cross bilateral filter

Yu Qiu, Kiichi Urahama

Research output: Contribution to journalArticle

Abstract

We present the PCA self-cross bilateral filter for denois-ing multi-modal images. We firstly apply the principal component analysis for input multi-modal images. We next smooth the first principal component with a preliminary filter and use it as a supplementary image for cross bilateral filtering of input images. Among some preliminary filters, the undecimated wavelet transform is useful for effective denoising of various multi-modal images such as color, multi-lighting and medical images.

Original languageEnglish
Pages (from-to)1709-1712
Number of pages4
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE93-A
Issue number9
DOIs
Publication statusPublished - Sep 2010

Fingerprint

Bilateral Filter
Denoising
Principal component analysis
Wavelet transforms
Lighting
Color
Filter
Medical Image
Principal Components
Wavelet Transform
Principal Component Analysis
Filtering

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering
  • Applied Mathematics

Cite this

Denoising of multi-modal images with PCA self-cross bilateral filter. / Qiu, Yu; Urahama, Kiichi.

In: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol. E93-A, No. 9, 09.2010, p. 1709-1712.

Research output: Contribution to journalArticle

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