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Erschienen in:
2007 | OriginalPaper | Buchkapitel
Noise Removal from Images by Projecting onto Bases of Principal Components
verfasst von : Bart Goossens, Aleksandra Pižurica, Wilfried Philips
Erschienen in: Advanced Concepts for Intelligent Vision Systems
Verlag: Springer Berlin Heidelberg
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In this paper, we develop a new wavelet domain statistical model for the removal of stationary noise in images. The new model is a combination of local linear projections onto bases of Principal Components, that perform a dimension reduction of the spatial neighbourhood, while avoiding the ”curse of dimensionality”. The models obtained after projection consist of a low dimensional Gaussian Scale Mixtures with a reduced number of parameters. The results show that this technique yields a significant improvement in denoising performance when using larger spatial windows, especially on images with highly structured patterns, like textures.