An Ultra-Fast Image Simulation Technique with Spatially Variable Point Spread Functions

TL;DR

This paper presents a novel, fast image simulation method that accurately models spatially variable PSFs in astronomical images, avoiding boundary artifacts and improving simulation fidelity.

Contribution

It introduces a continuous PSF variation simulation technique using PSF bases and image bases, significantly enhancing speed and accuracy over traditional patch-based methods.

Findings

Achieves high-fidelity simulated images with spatially variable PSFs

Reduces convolution time compared to traditional patch-based methods

Eliminates boundary artifacts in simulated images

Abstract

Simulated images are essential in algorithm development and instrument testing for optical telescopes. During real observations, images obtained by optical telescopes are affected by spatially variable point spread functions (PSFs), a crucial effect requiring accurate simulation. Traditional methods segment images into patches, convolve patches with individual PSFs, and reassemble them as a whole image. Although widely used, these approaches suffer from slow convolution processes and reduced image fidelity due to abrupt PSF transitions between different patches. This paper introduces a novel method for generating simulated images with spatial continuously varying PSFs. Our approach firstly decomposes original images into PSF bases derived with the principal component analysis method. The entire image is then convolved with these PSF bases to create image bases. Finally, we multiply the coefficients of image bases with these image bases for each pixels and add the multiplication results along each pixel to obtain the final simulated image. Our method could generate high-fidelity simulated images with spatially variable PSFs without boundary artifacts. The method proposed in this paper significantly improves the speed of astronomical image simulation, potentially advancing observational astronomy and instrumental development.