{"url":"/task/sar-image-despeckling","name":"Sar Image Despeckling","slug":"sar-image-despeckling","description_markdown":"Despeckling is the task of suppressing speckle from Synthetic Aperture Radar (SAR) acquisitions.\r\n\r\nImage credits: GRD Sentinel-1 SAR image despeckled with [SAR2SAR-GRD](https://arxiv.org/abs/2102.00692)","categories":[{"name":"Computer Vision","url":"/area/computer-vision"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"derived"},"counts":{"papers_tagged":22,"papers_with_code":11,"benchmarks":0,"benchmark_tables_in_archive":0,"benchmark_tables_shown":0,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":0,"subtasks":0,"parent_tasks":1},"benchmarks":[],"datasets":[],"subtasks":[],"parent_tasks":[{"url":"/task/denoising","name":"Denoising"}],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":11,"of":11,"tagged_in_all":22,"items":[{"url":"/paper/sar2sar-a-self-supervised-despeckling","title":"SAR2SAR: a semi-supervised despeckling algorithm for SAR images","date":"2020-06-26","arxiv_id":"2006.15037","repositories_listed":5,"syntology":null},{"url":"/paper/sar-image-despeckling-using-a-convolutional","title":"SAR Image Despeckling Using a Convolutional Neural Network","date":"2017-06-02","arxiv_id":"1706.00552","repositories_listed":3,"syntology":null},{"url":"/paper/as-if-by-magic-self-supervised-training-of","title":"As if by magic: self-supervised training of deep despeckling networks with MERLIN","date":"2021-10-25","arxiv_id":"2110.13148","repositories_listed":2,"syntology":null},{"url":"/paper/deep-learning-based-speckle-filtering-for","title":"Deep Learning Based Speckle Filtering for Polarimetric SAR Images. Application to Sentinel-1","date":"2024-08-28","arxiv_id":"2408.15678","repositories_listed":1,"syntology":null},{"url":"/paper/transformer-based-sar-image-despeckling","title":"Transformer-based SAR Image Despeckling","date":"2022-01-23","arxiv_id":"2201.09355","repositories_listed":1,"syntology":null},{"url":"/paper/sar-image-despeckling-using-continuous","title":"SAR Image Despeckling Using Continuous Attention Module","date":"2021-12-02","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/despeckling-sentinel-1-grd-images-by-deep","title":"Despeckling Sentinel-1 GRD images by deep learning and application to narrow river segmentation","date":"2021-02-01","arxiv_id":"2102.00692","repositories_listed":1,"syntology":null},{"url":"/paper/speckle2void-deep-self-supervised-sar","title":"Speckle2Void: Deep Self-Supervised SAR Despeckling with Blind-Spot Convolutional Neural Networks","date":"2020-07-04","arxiv_id":"2007.02075","repositories_listed":1,"syntology":null},{"url":"/paper/sar-image-despeckling-by-deep-neural-networks","title":"SAR Image Despeckling by Deep Neural Networks: from a pre-trained model to an end-to-end training strategy","date":"2020-06-28","arxiv_id":"2006.15559","repositories_listed":1,"syntology":null},{"url":"/paper/guided-patch-wise-nonlocal-sar-despeckling","title":"Guided patch-wise nonlocal SAR despeckling","date":"2018-11-28","arxiv_id":"1811.11872","repositories_listed":1,"syntology":null},{"url":"/paper/learning-a-dilated-residual-network-for-sar","title":"Learning a Dilated Residual Network for SAR Image Despeckling","date":"2017-09-09","arxiv_id":"1709.02898","repositories_listed":1,"syntology":null}],"syntology_records":0,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-25T09:33:49+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}