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. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Aujol, J. F., Aubert, G., Blanc-Féraud, L., & Chambolle, A. (2003). Image decomposition application to SAR images. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2695, 297–312. https://doi.org/10.1007/3-540-44935-3_21
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