Related papers: Wavelets, Curvelets and Multiresolution Analysis T…
The signatures of waves are seen during many high-quality ground-based refractive stellar occultations by solar system atmospheres. We present a new forward-modeling technique for ground-based stellar occultations based on wavelet…
Breast cancer is in the most common malignant tumor in women. It accounted for 30% of new malignant tumor cases. Although the incidence of breast cancer remains high around the world, the mortality rate has been continuously reduced. This…
Coronal mass ejections (CMEs) are large-scale eruptions of plasma and magnetic feld that can produce adverse space weather at Earth and other locations in the Heliosphere. Due to the intrinsic multiscale nature of features in coronagraph…
Neural Radiance Field (NeRF) has shown impressive performance in novel view synthesis via implicit scene representation. However, it usually suffers from poor scalability as requiring densely sampled images for each new scene. Several…
Deep learning is an increasingly popular approach for inverting surface wave dispersion curves to obtain Vs profiles. However, its generalizability is constrained by the depth and velocity scales of training data. We propose a unified deep…
Tomographic reconstruction is an ill-posed inverse problem that calls for regularization. One possibility is to require sparsity of the unknown in an orthonormal wavelet basis. This in turn can be achieved by variational regularization…
We propose new methodologies in multi-dimensional unfolding in dense environments, and show that incorporating auxiliary observables can significantly improve performance. Our approach builds on the ML-based OmniFold algorithm, which we…
Although deep convolutional neural networks have achieved remarkable success in removing synthetic fog, it is essential to be able to process images taken in complex foggy conditions, such as dense or non-homogeneous fog, in the real world.…
We demonstrate how the image analysis technique of wavelet decomposition can be applied to the gamma-ray sky to separate emission on different angular scales. New structures on scales that differ from the scales of the conventional…
Context: The detection and identification of oscillation modes (in terms of their $\ell$, $m$ and successive $n$) is a great challenge for present and future asteroseismic space missions. The "peak tagging" is an important step in the…
This paper is concerned with density estimation of directional data on the sphere. We introduce a procedure based on thresholding on a new type of spherical wavelets called {\it needlets}. We establish a minimax result and prove its…
Ablation fronts and shocks are two radiative/hydrodynamic features ubiquitous in inertial confinement fusion (ICF). A specially designed shock-tube experiment was tested on the OMEGA laser facility to observe these two features evolve at…
We present a comprehensive study of interstellar X-ray extinction using the extensive Chandra supernova remnant archive and use our results to refine the empirical relation between the hydrogen column density and optical extinction. In our…
Velocity measurements made from multiple-epoch astronomical images of evolving objects with optically thin continuum emission (e.g. as relativistic jets or expanding supernova shells) may be confused as a result of the overlap of…
We conduct a statistical analysis of the factors responsible for the variation in the ionization parameter (U) of high-redshift star-forming galaxies based on medium resolution JWST/NIRSpec observations obtained by the Cosmic Evolution…
Two-dimensional space-resolved temperature and density images of an inertial confinement fusion (ICF) implosion core have been diagnosed for the first time. Argon-doped, direct-drive ICF experiments were performed at the Omega Laser…
Defect detection by ultrasonic method is limited by the pulse width. Resolution can be improved through a deconvolution process with a priori information of the pulse or by its estimation. In this paper a regularization of the Wiener filter…
We investigate the use of wavelet-space feature decomposition in neural super-resolution for rendering pipelines. Building on recent neural upscaling frameworks, we introduce a formulation that predicts stationary wavelet coefficients…
Dense pixelwise prediction such as semantic segmentation is an up-to-date challenge for deep convolutional neural networks (CNNs). Many state-of-the-art approaches either tackle the loss of high-resolution information due to pooling in the…
We have developed a regularisation procedure for the direct deprojection and PSF-deconvolution of X-ray surface brightness profiles of clusters of galaxies. This procedure allows us to obtain accurate density profiles in a straightforward…