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Previous studies determining which astronomical photometry software is best suited for a particular dataset are usually focused on speed, source classification, and/or meeting a sensitivity requirement. For faint objects in particular, the…
We introduce a new algorithm for interpolating measurements of the point-spread function (PSF) using stars from many exposures. The principal components of the variation in the PSF pattern from multiple exposures are used to solve for…
We propose a few-shot learning method for spatial regression. Although Gaussian processes (GPs) have been successfully used for spatial regression, they require many observations in the target task to achieve a high predictive performance.…
We propose a new technique for adaptive identification of sparse systems based on the compressed sensing (CS) theory. We manipulate the transmitted pilot (input signal) and the received signal such that the weights of adaptive filter…
The analysis of adaptive carrier phase estimation is investigated in long-haul high speed n-level phase shift keying (n-PSK) optical fiber communication systems based on the one-tap normalized least-mean-square (LMS) algorithm. The…
Even though the technology of adaptive optics (AO) is rapidly maturing, calibration of the resulting images remains a major challenge. The AO point-spread function (PSF) changes quickly both in time and position on the sky. In a typical…
We have developed a new technique for weak lensing analysis, with which the effect of the point spread function (PSF) on small galaxy images can be corrected for accurately. Rather than relying on weighted second moments of detected images,…
The Spatial Sensitivity Function (SSF) is used to quantify a detector's sensitivity to a spatially-distributed input signal. By weighting the incoming signal with the SSF and integrating, the overall scalar response of the detector can be…
The ability to accurately measure the shapes of faint objects in images taken with the Advanced Camera for Surveys(ACS) on the Hubble Space Telescope (HST) depends upon detailed knowledge of the Point Spread Function (PSF). We show that…
We propose and examine the use of biphoton pairs, such as those created in parametric down conversion or four-wave mixing, to enhance the precision and the resolution of measuring optical displacements by position-sensitive detection. We…
We report the application of machine learning to smartphone based colorimetric detection of pH values. The strip images were used as the training set for Least Squares-Support Vector Machine (LS-SVM) classifier algorithms that were able to…
A prototype of a low cost Adaptive Optics (AO) system has been developed at the Instituto de Astrofisica de Andalucia (CSIC) and tested at the 2.2m telescope of the Calar Alto observatory. We present here the status of the project, which…
Few-shot segmentation performance declines substantially when facing images from a domain different than the training domain, effectively limiting real-world use cases. To alleviate this, recently cross-domain few-shot segmentation (CD-FSS)…
The performance of tip-enhanced optical microscopy is often limited by inefficient coupling of the excitation field to the plasmonic tip apex, as well as by thermal drift and optical aberrations. Here, we demonstrate that adaptive wavefront…
Non-Gaussian and multimodal distributions are an important part of many recent robust sensor fusion algorithms. In difference to robust cost functions, they are probabilistically founded and have good convergence properties. Since their…
This paper introduces a novel adaptive framework for processing dynamic flow signals over simplicial complexes, extending classical least-mean-squares (LMS) methods to high-order topological domains. Building on discrete Hodge theory, we…
The design of the camera and optical measurement is a crucial part of optimizing machine vision systems. However, camera designs are usually optimized to produce human-interpretable images. Moreover, camera optimization typically makes the…
Lightness adaptation is vital to the success of image processing to avoid unexpected visual deterioration, which covers multiple aspects, e.g., low-light image enhancement, image retouching, and inverse tone mapping. Existing methods…
We propose an adaptive Metropolis-Hastings algorithm in which sampled data are used to update the proposal distribution. We use the samples found by the algorithm at a particular step to form the information-theoretically optimal mean-field…
Neglecting the second order corrections in weak lensing measurements can lead to a few percent uncertainties on cosmic shears, and becomes more important for cluster lensing mass reconstructions. Existing methods which claim to measure the…