Related papers: WARP: The Data Reduction Pipeline for the WINERED …
To achieve its ambitious scientific goals, the Near-Infrared Spectrograph, NIRSpec, on board the Webb Space Telescope, needs to meet very demanding throughput requirements, here quantified in terms of photon-conversion efficiency (PCE).…
Processing of raw data from modern astronomical instruments is nowadays often carried out using dedicated software, so-called "pipelines" which are largely run in automated operation. In this paper we describe the data reduction pipeline of…
SIPGI is a spectroscopic pipeline for the data reduction of optical/near-infrared data acquired by slit-based spectrographs. SIPGI is a complete spectroscopic data reduction environment retaining the high level of flexibility and accuracy…
We describe the data processing pipeline developed to reduce the pointing observation data of Lunar-based Ultraviolet Telescope (LUT), which belongs to the Chang'e-3 mission of the Chinese Lunar Exploration Program. The pointing observation…
We introduce a camera pipeline for rendering visually pleasing photographs in low light conditions, as part of the NTIRE2022 Night Photography Rendering challenge. Given the nature of the task, where the objective is verbally defined by an…
The WMAP 7-year temperature maps have been re-analized to extract a CMB map and CMB power spectrum with reduced contamination by astrophysical foregrounds and noise. The method used is based on linear combinations of WMAP data and…
We developed a Python based framework for astronomical image processing and analysis. Astronomical image loading, normalizing, stacking, and filtering processes represent visible range images from grayscale. Besides, the blending process…
The large data size and dimensionality of hyperspectral data demands complex processing and data analysis. Multispectral data do not suffer the same limitations, but are normally restricted to blue, green, red, red edge, and near infrared…
We describe an algorithm to optimally extract individual spectra of blended sources from a long slit spectrum. A semi-analytic model for the spatial profile is used: a Voigt profile for the undersampled core with a numerical correction…
Here we present an automated method for obtaining wavelength calibrations for one-dimensional spectra, using Dynamic Time Warping (DTW). DTW is a flexible and well-understood algorithm for pattern matching, which has not been widely used in…
Ground-based high-resolution spectra provide a powerful tool for characterising exoplanet atmospheres. However, they are greatly hampered by the dominating telluric and stellar lines, which need to be removed prior to any analysis. Such…
Multiple low-vision tasks such as denoising, deblurring and super-resolution depart from RGB images and further reduce the degradations, improving the quality. However, modeling the degradations in the sRGB domain is complicated because of…
The price of instruments and observing time on modern telescopes is quickly increasing with the size of the primary mirror. Therefore, it is worth revisiting the data reduction algorithms to extract every bit of scientific information from…
The incorporation of LiDAR technology into some high-end smartphones has unlocked numerous possibilities across various applications, including photography, image restoration, augmented reality, and more. In this paper, we introduce a novel…
Efficient data annotation stands as a significant bottleneck in training contemporary machine learning models. The Programmatic Weak Supervision (PWS) pipeline presents a solution by utilizing multiple weak supervision sources to…
Reliable parameter extraction from experimental data is central to quantitative analysis in spectroscopy, diffraction, photoluminescence, chromatography, microscopy, and time-resolved measurements. We present FitED, a Python-based desktop…
Wavelength calibration is a routine and critical part of any spectral work-flow, but many astronomers still resort to matching detected peaks and emission lines by hand. We present RASCAL (RANSAC Assisted Spectral CALibration), a python…
Ultrafast Plane-Wave (PW) imaging often produces artifacts and shadows that vary with insonification angles. We propose a novel approach using Implicit Neural Representations (INRs) to compactly encode multi-planar sequences while…
We present the Spectral Image Typer (SPIT), a convolutional neural network (CNN) built to classify spectral images. In contrast to traditional, rules-based algorithms which rely on meta data provided with the image (e.g. header cards), SPIT…
Wide-angle light scattering (WALS) offers the possibility of a highly temporally and spatially resolved measurement of droplets in spray-based methods for nanoparticle synthesis. The size of these droplets is a critical variable affecting…