A new deconvolution algorithm separates AGN host galaxies from central point sources via smoothness, sparsity, and a pixel-wise product balance constraint, achieving HST-comparable resolution on Subaru HSC data.
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Neo, a cGAN, super-resolves HSC images to HST-like quality and improves galaxy morphological parameter accuracy by factors of 2-10.
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A New PSF Deconvolution Algorithm: Simultaneous Spatial Resolution Enhancement and Point Source Removal for Morphological Analysis of AGN Host Galaxies
A new deconvolution algorithm separates AGN host galaxies from central point sources via smoothness, sparsity, and a pixel-wise product balance constraint, achieving HST-comparable resolution on Subaru HSC data.
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Photometric Super-Resolution for Improving Galaxy Morphological Measurements using Conditional Generative Adversarial Networks
Neo, a cGAN, super-resolves HSC images to HST-like quality and improves galaxy morphological parameter accuracy by factors of 2-10.