Dynamic Texture Extraction and Video Denoising

According to recent works, introduced by Y.Meyer [1] the decomposition models based on Total Variation (TV) appear as a very good way to extract texture from image sequences. Indeed, videos show up characteristic variations along the temporal dimension which can be catched in the decomposition framework. However, there are very few works in literature which deal with spatio-temporal decompositions. Thus, we devote this paper to spatio-temporal extension of the spatial color decomposition model. We provide a relevant method to accurately catch Dynamic Textures (DT) present in videos. Moreover, we obtain the spatio-temporal regularized part (the geometrical component), and we distinctly separate the highly oscillatory variations, (the noise). Furthermore, we present some elements of comparison between several models in denoising purpose.

• Type: Conference
• Year: 2009
• Where: ACIVS
• Authors: Mathieu Lugiez, Michel Ménard, Abdallah El-Hamidi
• Keywords: ACIVS 2009, Computer Vision, Decomposition Model, Spatial Color Decomposition, Spatio-temporal Decompositions