OPTIMALLY SPARSE IMAGE REPRESENTATION BY THE EASY PATH WAVELET TRANSFORM

摘要

The Easy Path Wavelet Transform (EPWT),20 has recently been proposed by one of thenauthors as a tool for sparse representations of bivariate functions from discrete data, innparticular from image data. The EPWT is a locally adaptive wavelet transform. It worksnalong pathways through the array of function values and it exploits the local correlationsnof the given data in a simple appropriate manner. In this paper, we show that thenEPWT leads, for a suitable choice of the pathways, to optimal N-term approximationsnfor piecewise H¨older continuous functions with singularities along curves.