Related papers: MegaPipe: the MegaCam image stacking pipeline at t…

Biologists all over the world use camera traps to monitor biodiversity and wildlife population density. The computer vision community has been making strides towards automating the species classification challenge in camera traps, but it…

We introduce new methods for robust high-precision photometry from well-sampled images of a non-crowded field with a strongly varying point-spread function. For this work, we used archival imaging data of the open cluster M37 taken by MMT…

For many computer vision applications, the availability of camera calibration data is crucial as overall quality heavily depends on it. While calibration data is available on some devices through Augmented Reality (AR) frameworks like…

The field of connectomics faces unprecedented "big data" challenges. To reconstruct neuronal connectivity, automated pixel-level segmentation is required for petabytes of streaming electron microscopy data. Existing algorithms provide…

We consider the problem of simultaneously estimating a dense depth map and camera pose for a large set of images of an indoor scene. While classical SfM pipelines rely on a two-step approach where cameras are first estimated using a bundle…

Context: Data from ground-based, high-resolution solar telescopes can only be used for science with calibrations and processing, which requires detailed knowledge about the instrumentation. [...] Aims: We aim to provide observers with a…

We present the TRansient Image Processing Pipeline (TRIPP), a transient and variable source detection pipeline that employs both difference imaging and light curve analysis techniques for astronomical data. Additionally, we demonstrate…

The Combined Array for Millimeter-wave Astronomy (CARMA) data reduction pipeline (CADRE) has been developed to give investigators a first look at a fully reduced set of their data. It runs automatically on all data produced by the telescope…

Deep astronomical images are often constructed by digitially stacking many individual sub-exposures. Each sub-exposure is expected to show small differences in the positions of stars and other objects in the field, due to the movement of…

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 central institute of electronics (ZEA-2) in the Forschungszentrum Juelich (FZJ) has developed a system to scan the response of the photocathode of photomultiplier tubes (PMT). The PMT sits tight on a supporting structure, while a blue…

Recent advances in Computer Vision and Deep Learning have enabled astonishing results in a variety of fields and applications. Motivated by this success, the SkyCam Dataset aims to enable image-based Deep Learning solutions for short-term,…

This paper describes the search for an alternative approach to the automatic categorization of camera trap images. First, we benchmark state-of-the-art classifiers using a single model for all images. Next, we evaluate methods combining…

In this study we present a two-step map/reduce framework to stitch satellite mosaic images. The proposed system enable recognition and extraction of objects whose parts falling in separate satellite mosaic images. However this is a time and…

Image matching is a classic and fundamental task in computer vision. In this paper, under the hypothesis that the areas outside the co-visible regions carry little information, we propose a matching key-points crop (MKPC) algorithm. The…

The Montage image mosaic engine has found wide applicability in astronomy research, integration into processing environments, and is an examplar application for the development of advanced cyber-infrastructure. It is written in C to provide…

Video Captioning (VC) is a challenging multi-modal task since it requires describing the scene in language by understanding various and complex videos. For machines, the traditional VC follows the…

The NectarCAM is a camera that will be mounted on the Medium-Sized Telescopes of the Cherenkov Telescope Array (CTA) observatory. Along with the hardware integration of the camera, the scientific software, $\texttt{nectarchain}$, is being…

We describe a compression method for floating-point astronomical images that gives compression ratios of 6 -- 10 while still preserving the scientifically important information in the image. The pixel values are first preprocessed by…

The Kepler Mission Science Operations Center (SOC) performs several critical functions including managing the ~156,000 target stars, associated target tables, science data compression tables and parameters, as well as processing the raw…