Related papers: Light Source Point Cluster Selection Based Atmosph…
Image clustering is a very useful technique that is widely applied to various areas, including remote sensing. Recently, visual representations by self-supervised learning have greatly improved the performance of image clustering. To…
Automatic image clustering is a cornerstone of computer vision, yet its application to image enhancement remains limited, primarily due to the difficulty of defining clusters that are meaningful for this specific task. To address this…
There is an extensive set of methods to determine sparse sources from mixtures where the mixing coefficients are unknown. Each method involves plotting N sets of mixed data against each other in N-dimensional space. In the approach adopted…
The Northern Sky Optical Cluster Survey is a project to create an objective catalog of galaxy clusters over the entire high-galactic-latitude Northern sky, with well understood selection criteria. We use the object catalogs generated from…
The Density Based Spatial Clustering of Applications with Noise (DBSCAN) is a topometric algorithm used to cluster spatial data that are affected by background noise. For the first time, we propose the use of this method for the detection…
Illumination estimation is often used in mixed reality to re-render a scene from another point of view, to change the color/texture of an object, or to insert a virtual object consistently lit into a real video or photograph. Specifically,…
In this paper we present a new dynamical systems algorithm for clustering in hyperspectral images. The main idea of the algorithm is that data points are \`pushed\' in the direction of increasing density and groups of pixels that end up in…
Estimating the true background in an astronomical image is fundamental to detecting faint sources. In a typical low-photon count astronomical image, such as in the far and near-ultraviolet wavelength range, conventional methods relying on…
A new method for improving the resolution of astronomical images is presented. It is based on the principle that sampled data cannot be fully deconvolved without violating the sampling theorem. Thus, the sampled image should not be…
Illuminating a scene with artificial light is a prerequisite for seeing in dark environments. However, nonuniform and dynamic illumination can deteriorate or even break computer vision approaches, for instance when operating a robot with…
The aperture photometry method is a powerful tool that enables us to study large star cluster systems efficiently. However, its accuracy depends on various factors, including the stochasticity of the stellar initial mass function and…
In [1], a clustering algorithm was given to find the centers of clusters quickly. However, the accuracy of this algorithm heavily depend on the threshold value of d-c. Furthermore, [1] has not provided any efficient way to select the…
{The determination of cluster masses is a complex problem that would be aided by information about the cluster shape and orientation (along the line-of-sight).} {It is in this context, that we have developed a scheme for identifying the…
We present a novel algorithm for light source estimation in scenes reconstructed with a RGB-D camera based on an analytically-derived formulation of path-tracing. Our algorithm traces the reconstructed scene with a custom path-tracer and…
We show that the errors due to atmospheric refraction are present in the magnitudes determined with the Difference Images Analysis method. In case of single, unblended stars the size of the effect agrees with the theoretical prediction. But…
We present a novel approach to perform ground-based estimation and prediction of the surface solar irradiance with the view to predicting photovoltaic energy production. We propose the use of mini-batch k-means clustering to extract…
Particulate Matter (PM) is a form of air pollution that visually degrades urban scenery and is hazardous to human health and the environment. Current monitoring devices are limited in measuring average PM over large areas. Quantifying the…
The problem of resolving point-like light sources not only serves as a benchmark for optical resolution but also holds various practical applications ranging from microscopy to astronomy. In this research, we aim to resolve two thermal…
We present an algorithm capable of detecting diffuse, dim sources of any size in an astronomical image. These sources often defeat traditional methods for source finding, which expand regions around points of high intensity. Extended…
The low surface brightness (LSB) regime ($\mu_{g} \gtrsim 26$ mag arcsec$^{-2}$) comprises a vast, mostly unexplored discovery space, from dwarf galaxies to the diffuse interstellar medium. Accessing this regime requires precisely removing…