This paper introduces an adaptive, multi-resolution windowing technique that can be used in conjunction with the spatially localized spherical harmonic transform (SLSHT) to process signals on the 2-sphere in the spatio-spectral domain. In contrast with the standard formulation, which uses a fixed window, the new windowing technique is able to respond locally to the signal under analysis, that is, be adaptive, and also is formulated to depend on the spectral degree to give it a multi-resolution character. We further enhance its simultaneous spatial and spectral localization by basing the window on a parametric band-limited Slepian maximum spatial concentration eigenfunction. The criterion for window design is to maximize the energy concentra...
In this work, we design complete orthonormal basis functions, which are referred to as optimal basis...
Many factors existing in practical applications may limit the performance potential of a superresolu...
Abstract. We formulate and solve the Slepian spatial-spectral concentration problem on the three-dim...
This correspondence studies a spatially localized spectral transform for signals on the unit sphere,...
This paper presents a general framework for spatially-varying spectral filtering of signals defined ...
We propose a transform for signals defined on the sphere that reveals their localized directional co...
International audienceS U M M A R Y It is often advantageous to investigate the relationship between...
Abstract—We propose a transform for signals defined on the sphere that reveals their localized direc...
In this paper we show that the spatially localized spherical harmonic transform (SLSHT), which repre...
We propose a transform for signals defined on the sphere that reveals their localized directional co...
In this paper, we develop an analytical formulation for the Slepian spatial-spectral concentration p...
This paper investigates spectral filtering using isotropic spectral windows, which is a computationa...
In this paper, we present an optimal filter for the enhancement or estimation of signals on the 2-sp...
The problems of filtering, spectral analysis and spectral estimation have been investigated on the s...
We propose a transform for signals defined on the sphere that reveals their localized directional co...
In this work, we design complete orthonormal basis functions, which are referred to as optimal basis...
Many factors existing in practical applications may limit the performance potential of a superresolu...
Abstract. We formulate and solve the Slepian spatial-spectral concentration problem on the three-dim...
This correspondence studies a spatially localized spectral transform for signals on the unit sphere,...
This paper presents a general framework for spatially-varying spectral filtering of signals defined ...
We propose a transform for signals defined on the sphere that reveals their localized directional co...
International audienceS U M M A R Y It is often advantageous to investigate the relationship between...
Abstract—We propose a transform for signals defined on the sphere that reveals their localized direc...
In this paper we show that the spatially localized spherical harmonic transform (SLSHT), which repre...
We propose a transform for signals defined on the sphere that reveals their localized directional co...
In this paper, we develop an analytical formulation for the Slepian spatial-spectral concentration p...
This paper investigates spectral filtering using isotropic spectral windows, which is a computationa...
In this paper, we present an optimal filter for the enhancement or estimation of signals on the 2-sp...
The problems of filtering, spectral analysis and spectral estimation have been investigated on the s...
We propose a transform for signals defined on the sphere that reveals their localized directional co...
In this work, we design complete orthonormal basis functions, which are referred to as optimal basis...
Many factors existing in practical applications may limit the performance potential of a superresolu...
Abstract. We formulate and solve the Slepian spatial-spectral concentration problem on the three-dim...