Astronomical Image Processing with Array Detectors

TL;DR

This paper investigates methods for processing astronomical images obtained from array detectors, focusing on sampling, interpolation, and the impact of detector imperfections on image quality.

Contribution

It provides a detailed analysis of sampling strategies, interpolation kernels, and the effects of missing pixels in array detectors for astronomical imaging.

Findings

Interpolation normalization is crucial for irregular sampling.

Missing pixels affect Nyquist sampling criteria.

Analysis of idealized and realistic detector scenarios.

Abstract

We address the question of astronomical image processing from data obtained with array detectors. We define and analyze the cases of evenly, regularly, and irregularly sampled maps for idealized (i.e., infinite) and realistic (i.e., finite) detectors. We concentrate on the effect of interpolation on the maps, and the choice of the kernel used to accomplish this task. We show how the normalization intrinsic to the interpolation process must be carefully accounted for when dealing with irregularly sampled grids. We also analyze the effect of missing or dead pixels in the array, and their consequences for the Nyquist sampling criterion.