Robustly Adaptive Wavelet Filter Bank Using L1 Norm (CROSBI ID 574066)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Ana Sović ; Damir Seršić
engleski
Robustly Adaptive Wavelet Filter Bank Using L1 Norm
Sparse representation of signals is the key for many applications, such as denoising, compression, or compressive sensing. In this paper, we propose an original adaptive wavelet filter bank that, for a class of signals, provides better compaction of information. Previously reported 1D and 2D point-wise adaptive wavelets were based on minimization of the L2 error norm. Now, we introduce minimum of the L1 norm on a sliding window as the adaptation criterion. Its main advantages are robustness to outliers and sparser representation of the input data. The proposed algorithm was tested on synthetic signals. It shows significant improvement over known methods, which is paid with somewhat increased numerical complexity. Still, there is some room for improvements, by further development of the adaptive criterion and its efficient realization.
Adaptive wavelets; vanishing moments; minimum L1 criterion; LAD adaptation
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Podaci o prilogu
9-12.
2011.
objavljeno
Podaci o matičnoj publikaciji
Proceedings IWSSIP 2011
Branka Zovko-Cihlar, Narcis Behlilović, Mesud Hadžialić
Sarajevo: Faculty of Electrical Engineering, University Sarajevo, B40 d.o.o.
987-9958-9966-1-0
2157-8672
Podaci o skupu
18th International Conference on Systems, Signals and Image Processing
predavanje
16.06.2011-18.06.2011
Sarajevo, Bosna i Hercegovina