相关论文: Eliminating polarization leakage effect for neutra…

Recent denoising algorithms based on the "blind-spot" strategy show impressive blind image denoising performances, without utilizing any external dataset. While the methods excel in recovering highly contaminated images, we observe that…

In natural image matting, the goal is to estimate the opacity of the foreground object in the image. This opacity controls the way the foreground and background is blended in transparent regions. In recent years, advances in deep learning…

Blind cleaning methods are currently the preferred strategy for handling foreground contamination in single-dish HI intensity mapping surveys. Despite the increasing sophistication of blind techniques, some signal loss will be inevitable…

Hybrid Foreground Residual Subtraction (HyFoReS) is a new family of algorithms designed to remove systematics-induced foreground contamination for 21-cm intensity mapping data. Previously, the algorithm was shown to be effective in…

Integrating a foreground object into a background scene with illumination harmonization is an important but challenging task in computer vision and augmented reality community. Existing methods mainly focus on foreground and background…

Foreground contamination is the fundamental hindrance to the cosmic microwave background (CMB) signals and its separation from it represents a fundamental question in Cosmology. One of the most popular algorithm used to disentangle…

Intrinsic image decomposition (IID) is the task that decomposes a natural image into albedo and shade. While IID is typically solved through supervised learning methods, it is not ideal due to the difficulty in observing ground truth albedo…

Marine snow, the floating particles in underwater images, severely degrades the visibility and performance of human and machine vision systems. This paper proposes a novel method to reduce the marine snow interference using deep learning…

Experiments aimed at detecting highly-redshifted 21 centimeter emission from the Epoch of Reionization (EoR) are plagued by the contamination of foreground emission. A potentially important source of contaminating foregrounds may be…

Measuring one-point statistics in redshifted 21 cm intensity maps offers an opportunity to explore non-Gaussian features of the early universe. We assess the impact of instrumental effects on measurements made with the Hydrogen Epoch of…

Extragalactic foregrounds are known to generate significant biases in temperature-based CMB lensing reconstruction. Several techniques, which include ``source hardening'' and ``shear-only estimators'' have been proposed to mitigate…

Intensity mapping of 21cm emission from neutral hydrogen promises to be a powerful probe of large-scale structure in the post-reionisation epoch. However, HI intensity mapping (IM) experiments will suffer the loss of long-wavelength…

Intensity mapping of the HI 21 cm line and the CO 2.61 mm line from the epoch of reionization has emerged as powerful, complementary, probes of the high-redshift Universe. However, both maps and their cross-correlation are dominated by…

The fairness of a deep neural network is strongly affected by dataset bias and spurious correlations, both of which are usually present in modern feature-rich and complex visual datasets. Due to the difficulty and variability of the task,…

Computing polarised intensities from noisy data in Stokes U and Q suffers from a positive bias that should be suppressed. To develop a correction method that, when applied to maps, should provide a distribution of polarised intensity that…

We introduce a new implementation of the FastICA algorithm on simulated LOFAR EoR data with the aim of accurately removing the foregrounds and extracting the 21-cm reionization signal. We find that the method successfully removes the…

A key challenge for current and upcoming CMB lensing measurements is their sensitivity to biases from extragalactic foregrounds, such as Sunyaev-Zeldovich (SZ) signals or cosmic infrared background emission. Several methods have been…

One of the main obstacles for extracting the cosmic microwave background (CMB) signal from observations in the mm/sub-mm range is the foreground contamination by emission from Galactic component: mainly synchrotron, free-free, and thermal…

Single-image HDR reconstruction or inverse tone mapping (iTM) is a challenging task. In particular, recovering information in over-exposed regions is extremely difficult because details in such regions are almost completely lost. In this…

Extracting cosmological information from microwave sky observations requires accurate estimation of the underlying Cosmic Microwave Background (CMB) by removing foreground contamination, instrumental noise, and the effects of beam…