We construct an algorithm to split an image into a sum u + v of a bounded variation component and a component containing the textures and the noise. This decomposition is inspired from arecent work of Y. Meyer. We find this decomposition by minimizing a convex functional which depends on the two variables u and v, alternatively in each variable. Each minimization is based on a projection algorithm to minimize the total variation. We carry out the mathematical study of our method. We present some numerical results. In particular, we show how the u component can be used in nontextured SAR image restoration.
- Total variation minimization
- SAR images
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Aujol, JF., Aubert, G., Blanc-Féraud, L., Chambolle, A. (2003). Image Decomposition Application to SAR Images. In: Griffin, L.D., Lillholm, M. (eds) Scale Space Methods in Computer Vision. Scale-Space 2003. Lecture Notes in Computer Science, vol 2695. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44935-3_21
Publisher Name: Springer, Berlin, Heidelberg
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Online ISBN: 978-3-540-44935-5
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