With information and scale as central themes, this comprehensive survey explains how to
handle real problems in astronomical data analysis using a modern arsenal of powerful …

This book presents the state of the art in sparse and multiscale image and signal processing,
covering linear multiscale transforms, such as wavelet, ridgelet, or curvelet transforms, and …

Deconvolution problems occur in many fields of nonparametric statistics, for example,
density estimation based on contaminated data, nonparametric regression with errors-in …

Due to the low-cost and lightweight units, single-wavelength LiDAR bathymetric systems are
an ideal option for shallow-water (< 12 m) bathymetry. However, one disadvantage of such …

This thoroughly updated new edition presents state of the art sparse and multiscale image
and signal processing. It covers linear multiscale geometric transforms, such as wavelet …

Previously, the convergence analysis for linear statistical inverse problems has mainly
focused on spectral cut-off and Tikhonov-type estimators. Spectral cut-off estimators achieve …

We explain some basic theoretical issues regarding nonparametric statistics applied to
inverse problems. Simple examples are used to present classical concepts such as the …

Airborne light detection and ranging (LiDAR) bathymetry appears to be a useful technology
for bed topography mapping of non‐navigable areas, offering high data density and a high …

The paper presents a novel despeckling method, based on Daubechies complex wavelet
transform, for medical ultrasound images. Daubechies complex wavelet transform is used …

For regularly spaced one-dimensional data, wavelet shrinkage has proven to be a
compelling method for non-parametric function estimation. We create three new multiscale …