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

Park Hyun (Dept. of Computer Science and Engineering, Hanyang University)
Moon Young-Shik (Dept. of Computer Science and Engineering, Hanyang University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.43, no.2, 2006 , pp. 63-71 More about this Journal
Abstract
Denoising and reconstruction of color images are extensively studied in the field of computer vision and image processing. Especially, denoising and reconstruction of color face images are more difficult than those of natural images because of the structural characteristics of human faces as well as the subtleties of color interactions. In this paper, we propose a denoising method based on PCA reconstruction for removing complex color noise on human faces, which is not easy to remove by using vectorial color filters. The proposed method is composed of the following five steps: training of canonical eigenface space using PCA, automatic extraction of facial features using active appearance model, relishing of reconstructed color image using bilateral filter, extraction of noise regions using the variance 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 complex color noise.
Keywords
Denoising; Reconstruction; Relighting; Blending;
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