Compute inverse (adjoint) SGWT for signal f (without frame calculation). The calculation is perform for the frame defined by the `tight_frame` function. The tightness of the underlying frame implies that the computation is obtained by simply applying the adjoint linear transformation to the wavelet coefficients.
inverse_sgwt(wc, evalues, evectors, b = 2)
Wavelet coefficients.
Eigenvalues of the Laplacian matrix.
Eigenvectors of the Laplacian matrix.
Parameter that control the number of scales.
f
SGWT adjoint applied to wc.
G<U+00F6>bel, F., Blanchard, G., von Luxburg, U. (2018). Construction of tight frames on graphs and application to denoising. In Handbook of Big Data Analytics (pp. 503-522). Springer, Cham.
de Loynes, B., Navarro, F., Olivier, B. (2021). Data-driven thresholding in denoising with Spectral Graph Wavelet Transform. Journal of Computational and Applied Mathematics, Vol. 389.
Hammond, D. K., Vandergheynst, P., & Gribonval, R. (2011). Wavelets on graphs via spectral graph theory. Applied and Computational Harmonic Analysis, 30(2), 129-150.