A Comparative Study of Wiener, Richardson-Lucy, and Total Variation Techniques for Astronomical Images^*

Astronomical images captured by ground-based telescopes are often degraded by atmospheric disturbances, commonly known as the "seeing effect," which causes significant blurring. Addressing this challenge, this study explores the efficacy of three deconvolution techniques—Wiener Deconvolution, Richardson-Lucy Deconvolution (RL), and Total Variation Deconvolution (TV)—on astronomical images. To facilitate a controlled comparison, this research utilized ten high-quality images from the Hubble Space Telescope (HST), which inherently lack atmospheric seeing effects. These images were artificially blurred using an Airy Point Spread Function (PSF) to simulate ground-based observations. The performance of each deconvolution method was rigorously evaluated using two well-established metrics: Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM). The results indicate that Wiener Deconvolution outperforms the other techniques in terms of both SSIM and PSNR, making it a superior choice for correcting blur in astronomical images.