fiDrizzle-MU: A Fast Iterative Drizzle with Multiplicative Updates
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866914155946049536 |
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| author | Zhang, Shen Wang, Lei Shan, Huanyuan Li, Ran Cao, Xiaoyue Gao, Yunhao |
| author_facet | Zhang, Shen Wang, Lei Shan, Huanyuan Li, Ran Cao, Xiaoyue Gao, Yunhao |
| contents | We propose fiDrizzleMU, an algorithm for co-adding exposures via iterative multiplicative updates, replacing the additive correction framework. This method achieves superior anti-aliasing and noise reduction in stacked images. When applied to James Webb Space Telescope data, the fiDrizzleMU algorithm reconstructs a gravitational lensing candidate that was significantly blurred by the pipeline's resampling process. This enables the accurate recovery of faint and extended structures in high-resolution astronomical imaging. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_09881 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | fiDrizzle-MU: A Fast Iterative Drizzle with Multiplicative Updates Zhang, Shen Wang, Lei Shan, Huanyuan Li, Ran Cao, Xiaoyue Gao, Yunhao Instrumentation and Methods for Astrophysics We propose fiDrizzleMU, an algorithm for co-adding exposures via iterative multiplicative updates, replacing the additive correction framework. This method achieves superior anti-aliasing and noise reduction in stacked images. When applied to James Webb Space Telescope data, the fiDrizzleMU algorithm reconstructs a gravitational lensing candidate that was significantly blurred by the pipeline's resampling process. This enables the accurate recovery of faint and extended structures in high-resolution astronomical imaging. |
| title | fiDrizzle-MU: A Fast Iterative Drizzle with Multiplicative Updates |
| topic | Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2511.09881 |