Footprints and edgeprints for image denoising and compression
Pier Luigi Dragotti, Martin Vetterli · 2002
Wavelets have been quite successful in compression or denoising applications. To further improve the performance of wavelet based algorithms, we have recently introduced the notion of footprint, which is a data structure which contains all the wavelet coefficients generated by a discontinuity. The combined use of wavelets and footprints leads to very efficient algorithms for compression and denoising of 1D piecewise smooth signals. We extend some of the previous results by presenting a new denoising algorithm, where footprints are chosen adaptively according to the singularity locations. This new algorithm outperforms previously proposed ones. Then, we introduce the notion of edgeprints, which represents a natural extension of footprints to the two dimensional case. First experimental results on the compression of 2D piecewise smooth signals using edgeprints are promising.