Multi-Modal Transformer for Compressive LiDARs Using Hyperspectral Imaging Side-Information
Compressive satellite LiDAR (CS-LiDAR) has been recently introduced as a radically different computational sensing and reconstruction approach for LiDAR sensing of Earth. It is based on NASA's adaptive wavelength scanning LiDAR (AWSL) system. Unlike conventional 1D LiDAR methods, CS-LiDAR utili...
Uloženo v:
| Vydáno v: | IEEE International Geoscience and Remote Sensing Symposium proceedings s. 2451 - 2454 |
|---|---|
| Hlavní autoři: | , , , , , , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
07.07.2024
|
| Témata: | |
| ISSN: | 2153-7003 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | Compressive satellite LiDAR (CS-LiDAR) has been recently introduced as a radically different computational sensing and reconstruction approach for LiDAR sensing of Earth. It is based on NASA's adaptive wavelength scanning LiDAR (AWSL) system. Unlike conventional 1D LiDAR methods, CS-LiDAR utilizes sparse coded laser illumination across a 2D field-of-view. The aim is to compressively capture Earth from hundreds of kilometers above, enabling computational 3D imagery reconstruction with resolution that is comparable to that attained with data collected from just hundreds of meters. The forward imaging model captures the light propagation phenomena affecting the photon pulses transmitted from the sensor to the Earth's surface and back. This work enhances CS-LiDAR by integrating imaging spectroscopy into a multimodal system and employing a transformer network for the inverse imaging problem, driven by multimodal attention mechanisms. Emulations enabled by enormous observational LiDAR data of Earth, available from NASA's G-LiHT imaging observatory, highlight the efficacy of methods developed. |
|---|---|
| AbstractList | Compressive satellite LiDAR (CS-LiDAR) has been recently introduced as a radically different computational sensing and reconstruction approach for LiDAR sensing of Earth. It is based on NASA's adaptive wavelength scanning LiDAR (AWSL) system. Unlike conventional 1D LiDAR methods, CS-LiDAR utilizes sparse coded laser illumination across a 2D field-of-view. The aim is to compressively capture Earth from hundreds of kilometers above, enabling computational 3D imagery reconstruction with resolution that is comparable to that attained with data collected from just hundreds of meters. The forward imaging model captures the light propagation phenomena affecting the photon pulses transmitted from the sensor to the Earth's surface and back. This work enhances CS-LiDAR by integrating imaging spectroscopy into a multimodal system and employing a transformer network for the inverse imaging problem, driven by multimodal attention mechanisms. Emulations enabled by enormous observational LiDAR data of Earth, available from NASA's G-LiHT imaging observatory, highlight the efficacy of methods developed. |
| Author | Arce, G. R. Porras-Diaz, N. Vargas, R. Ramirez-Jaime, A. Harding, D. Stephen, M. MacKinnon, J. |
| Author_xml | – sequence: 1 givenname: N. surname: Porras-Diaz fullname: Porras-Diaz, N. organization: University of Delaware, ECE – sequence: 2 givenname: A. surname: Ramirez-Jaime fullname: Ramirez-Jaime, A. organization: University of Delaware, ECE – sequence: 3 givenname: G. R. surname: Arce fullname: Arce, G. R. organization: University of Delaware, ECE – sequence: 4 givenname: R. surname: Vargas fullname: Vargas, R. organization: University of Delaware, PaSS – sequence: 5 givenname: D. surname: Harding fullname: Harding, D. organization: NASA, GSFC – sequence: 6 givenname: M. surname: Stephen fullname: Stephen, M. organization: NASA, GSFC – sequence: 7 givenname: J. surname: MacKinnon fullname: MacKinnon, J. organization: NASA, GSFC |
| BookMark | eNo1kMtOwzAQRQ0Cibb0D1iED0gZe-zEXlYF2kitkPpYsajcZFIZNQ_ZAal_31TAZs7oXs1ZzJDd1U1NjD1zmHAO5iWbT9ebjUKZqokAISccEsmlNDdsbFKjUQEmgELdsoHgCuMUAB_YMISvftECYMA-V9-nzsWrprCnaOttHcrGV-SjHtGsqVpPIbgfipbudboO0S64-hgtzi350FLe-f4sq-zxmm5cQXFWXwW2c039yO5Lewo0_uOI7d7ftrNFvPyYZ7PpMnY8TbrYpsDzhKPNe5jSaM25yukgDCUorJSQHFRZoMEDJ6JSadRQaE39KDgKHLGnX6_r633rXWX9ef__DLwABvpXBA |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IH CBEJK RIE RIO |
| DOI | 10.1109/IGARSS53475.2024.10641449 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Proceedings Order Plan (POP) 1998-present by volume IEEE Xplore All Conference Proceedings IEEE IEEE Proceedings Order Plans (POP) 1998-present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Geology |
| EISBN | 9798350360325 |
| EISSN | 2153-7003 |
| EndPage | 2454 |
| ExternalDocumentID | 10641449 |
| Genre | orig-research |
| GroupedDBID | 6IE 6IF 6IH 6IK 6IL 6IM 6IN AAJGR AAWTH ADZIZ ALMA_UNASSIGNED_HOLDINGS BEFXN BFFAM BGNUA BKEBE BPEOZ CBEJK CHZPO IPLJI OCL RIE RIL RIO RNS |
| ID | FETCH-LOGICAL-i176t-a701c613ac1c69f988115ceb29e632a4406b5fd393b1eeef58380d88e0d8d1323 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 3 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001316158502192&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| IngestDate | Wed Aug 27 02:03:01 EDT 2025 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i176t-a701c613ac1c69f988115ceb29e632a4406b5fd393b1eeef58380d88e0d8d1323 |
| PageCount | 4 |
| ParticipantIDs | ieee_primary_10641449 |
| PublicationCentury | 2000 |
| PublicationDate | 2024-July-7 |
| PublicationDateYYYYMMDD | 2024-07-07 |
| PublicationDate_xml | – month: 07 year: 2024 text: 2024-July-7 day: 07 |
| PublicationDecade | 2020 |
| PublicationTitle | IEEE International Geoscience and Remote Sensing Symposium proceedings |
| PublicationTitleAbbrev | IGARSS |
| PublicationYear | 2024 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| SSID | ssj0038200 |
| Score | 1.8979386 |
| Snippet | Compressive satellite LiDAR (CS-LiDAR) has been recently introduced as a radically different computational sensing and reconstruction approach for LiDAR... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 2451 |
| SubjectTerms | Adaptation models Earth Hyperspectral Image coding Imaging Laser radar LiDAR Machine Learning Side information Three-dimensional displays Training Transformers |
| Title | Multi-Modal Transformer for Compressive LiDARs Using Hyperspectral Imaging Side-Information |
| URI | https://ieeexplore.ieee.org/document/10641449 |
| WOSCitedRecordID | wos001316158502192&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LSwMxEA5aVDz5qvgmgtfU7Sa7SY5F7QNqKW2FgoeS7E5hQVvZPsB_7yTdVTx48JKEQFg2Q_bLtzPfDCF3RqhUS7AssbFlQoQJU8pYZjgYl83bWvBC4a7s9dR4rPuFWN1rYQDAB59BzQ29Lz-dJyv3qwxPeCyQAOhtsi1lvBFrlZ9djlAW7JHbIonmfafVGAyHERcyQhYYilq5-FcZFY8izYN_Pv-QVH_0eLT_jTRHZAtmx2S35Yvyfp6QV6-iZc_z1LzRUXkThZxiR92B97Gua6Dd7LExWFAfJkDbyEA3Qsscl3XefbkiOsxSYIVGydmsSl6aT6OHNiuKJrCsLuMlMzKoJ4jRJsFOT7VSeOdLkD9riHloBAK4jaYp19zW8QWnzm0apEoBNilSU35KKrP5DM4ItSIQNohDbRDnuYiNMqGNDIDigZWhPSdVt0eTj01ejEm5PRd_zF-SfWcJH-wqr0hlma_gmuwk62W2yG-8Nb8AC5mhXw |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1bS8MwFA46r0_eJt6N4Gu0a9I2eRzqLtiNsU0Y-DCS9gwKukl3Af-9J1mn-OCDL00pJCQ5pF--5HznEHKrhUxVBIYlJjRMCD9hUmrDNAdto3kbA04oHEftthwMVKcQqzstDAA45zO4s6_uLj-dJHN7VIYrPBRIANQ62QiwWW8p11r9eDmCmbdNboowmvfNerXb6wVcRAHyQF_crar_SqTicKS2988e7JPyjyKPdr6x5oCswfiQbNVdWt7PI_LqdLSsNUn1G-2v9qKQUyyoXfLO23UBNM4eq90pdY4CtIEcdCm1zLFa890lLKK9LAVWqJSs1crkpfbUf2iwIm0CyypROGM68ioJorROsFAjJSXu-hJk0ApC7muBEG6CUcoVNxUc4MhenHqplICPFMkpPyal8WQMJ4Qa4Qnjhb7SiPRchFpq3wQaQHLPRL45JWU7R8OPZWSM4Wp6zv74fk12Gv1WPIyb7edzsmut4lxfowtSmuVzuCSbyWKWTfMrZ9kvoG2kpg |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=IEEE+International+Geoscience+and+Remote+Sensing+Symposium+proceedings&rft.atitle=Multi-Modal+Transformer+for+Compressive+LiDARs+Using+Hyperspectral+Imaging+Side-Information&rft.au=Porras-Diaz%2C+N.&rft.au=Ramirez-Jaime%2C+A.&rft.au=Arce%2C+G.+R.&rft.au=Vargas%2C+R.&rft.date=2024-07-07&rft.pub=IEEE&rft.eissn=2153-7003&rft.spage=2451&rft.epage=2454&rft_id=info:doi/10.1109%2FIGARSS53475.2024.10641449&rft.externalDocID=10641449 |