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Automatic Denoising of 2D Color Face Images Using Recursive PCA Reconstruction

Title
Automatic Denoising of 2D Color Face Images Using Recursive PCA Reconstruction
Author
문영식
Keywords
Impulse Noise; Bilateral Filter; Denoising Method; Reconstructed Face; Input Face
Issue Date
2006-09
Publisher
SPRINGER-VERLAG BERLIN
Citation
International Conference on Advanced Concepts for Intelligent Vision Systems; ACIVS 2006: Advanced Concepts for Intelligent Vision Systems, Page. 799-809
Abstract
In this paper, we propose a denoising method based on PCA reconstruction for removing complex color noise components on human faces, which is not easy to remove by using vectorial color filters. The proposed method is composed of the following six steps: training of canonical eigenface space using PCA, automatic extraction of facial features using active appearance model and alignment of the input face to mean shape, reconstruction of an initial noise free face, relighting of reconstructed face using a bilateral filter, extraction of noise regions using the variances of skin color of training data, and reconstruction using partial information of input images (except the noise regions) and blending of the reconstructed image with the original image. Experimental results show that the proposed denoising method maintains the structural characteristics of input faces, while efficiently removing noise components with complex colors.
URI
https://link.springer.com/chapter/10.1007/11864349_73http://repository.hanyang.ac.kr/handle/20.500.11754/108490
ISBN
978-3-540-44630-9
DOI
10.1007/11864349_73
Appears in Collections:
COLLEGE OF COMPUTING[E] > COMPUTER SCIENCE(소프트웨어학부) > Articles
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