A robust framework for removing G 0 distributed noise from Synthetic Aperture Radar images Article Swipe
Ragesh Rajan M
,
M. Vinayababu
,
Shilpa Suresh
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1080/23311916.2024.2359999
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1080/23311916.2024.2359999
Synthetic Aperture Radar (SAR) imagery finds widespread applications across engineering disciplines, encompassing vegetation surveys, biomass estimation, and weather-related investigations. However, two significant challenges hinder SAR image analysis: the inherent difficulty in visually interpreting SAR images and the adverse impact of multiplicative speckle noise. The proposed study introduces a robust framework for removing G 0 distributed noise from Synthetic Aperture Radar (SAR) images. This framework utilizes Bitonic preprocessing filters and SailFish optimization within the wavelet domain to address challenges in SAR image analysis, particularly the difficulty in visually interpreting SAR images and the impact of multiplicative speckle noise. By assessing noise distribution and applying denoising algorithms tailored to estimated noise distribution, the study overcomes limitations of linear filters by adopting Bitonic filters for effective preprocessing. Through parameter optimization using SailFish Optimization (SFO) and objective functions like Structural Similarity Index Measure (SSIM) and Edge Preservation Index (EPI), the proposed method outperforms conventional algorithms on both synthetic and real SAR data. Furthermore, for synthetic SAR data with noise modeled as G0 distributed, our approach provides a more realistic benchmark for comparison than existing methods.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1080/23311916.2024.2359999
- https://www.tandfonline.com/doi/pdf/10.1080/23311916.2024.2359999?needAccess=true
- OA Status
- gold
- References
- 62
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4399385463
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4399385463Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1080/23311916.2024.2359999Digital Object Identifier
- Title
-
A robust framework for removing G 0 distributed noise from Synthetic Aperture Radar imagesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-06-05Full publication date if available
- Authors
-
Ragesh Rajan M, M. Vinayababu, Shilpa SureshList of authors in order
- Landing page
-
https://doi.org/10.1080/23311916.2024.2359999Publisher landing page
- PDF URL
-
https://www.tandfonline.com/doi/pdf/10.1080/23311916.2024.2359999?needAccess=trueDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.tandfonline.com/doi/pdf/10.1080/23311916.2024.2359999?needAccess=trueDirect OA link when available
- Concepts
-
Synthetic aperture radar, Remote sensing, Computer science, Noise (video), Interferometric synthetic aperture radar, Radar imaging, Environmental science, Geology, Radar, Artificial intelligence, Telecommunications, Image (mathematics)Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
62Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4399385463 |
|---|---|
| doi | https://doi.org/10.1080/23311916.2024.2359999 |
| ids.doi | https://doi.org/10.1080/23311916.2024.2359999 |
| ids.openalex | https://openalex.org/W4399385463 |
| fwci | 0.0 |
| type | article |
| title | A robust framework for removing G 0 distributed noise from Synthetic Aperture Radar images |
| biblio.issue | 1 |
| biblio.volume | 11 |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10801 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 0.9994999766349792 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2202 |
| topics[0].subfield.display_name | Aerospace Engineering |
| topics[0].display_name | Synthetic Aperture Radar (SAR) Applications and Techniques |
| topics[1].id | https://openalex.org/T11038 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.9994000196456909 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2202 |
| topics[1].subfield.display_name | Aerospace Engineering |
| topics[1].display_name | Advanced SAR Imaging Techniques |
| topics[2].id | https://openalex.org/T10688 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9988999962806702 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1707 |
| topics[2].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[2].display_name | Image and Signal Denoising Methods |
| is_xpac | False |
| apc_list.value | 950 |
| apc_list.currency | GBP |
| apc_list.value_usd | 1165 |
| apc_paid.value | 950 |
| apc_paid.currency | GBP |
| apc_paid.value_usd | 1165 |
| concepts[0].id | https://openalex.org/C87360688 |
| concepts[0].level | 2 |
| concepts[0].score | 0.6794730424880981 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q740686 |
| concepts[0].display_name | Synthetic aperture radar |
| concepts[1].id | https://openalex.org/C62649853 |
| concepts[1].level | 1 |
| concepts[1].score | 0.5147285461425781 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q199687 |
| concepts[1].display_name | Remote sensing |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.4840192496776581 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C99498987 |
| concepts[3].level | 3 |
| concepts[3].score | 0.4833090305328369 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q2210247 |
| concepts[3].display_name | Noise (video) |
| concepts[4].id | https://openalex.org/C22286887 |
| concepts[4].level | 3 |
| concepts[4].score | 0.4597412049770355 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q1666056 |
| concepts[4].display_name | Interferometric synthetic aperture radar |
| concepts[5].id | https://openalex.org/C10929652 |
| concepts[5].level | 3 |
| concepts[5].score | 0.41196727752685547 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q7279985 |
| concepts[5].display_name | Radar imaging |
| concepts[6].id | https://openalex.org/C39432304 |
| concepts[6].level | 0 |
| concepts[6].score | 0.3660491406917572 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q188847 |
| concepts[6].display_name | Environmental science |
| concepts[7].id | https://openalex.org/C127313418 |
| concepts[7].level | 0 |
| concepts[7].score | 0.35789138078689575 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q1069 |
| concepts[7].display_name | Geology |
| concepts[8].id | https://openalex.org/C554190296 |
| concepts[8].level | 2 |
| concepts[8].score | 0.3454247713088989 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q47528 |
| concepts[8].display_name | Radar |
| concepts[9].id | https://openalex.org/C154945302 |
| concepts[9].level | 1 |
| concepts[9].score | 0.3220348358154297 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[9].display_name | Artificial intelligence |
| concepts[10].id | https://openalex.org/C76155785 |
| concepts[10].level | 1 |
| concepts[10].score | 0.17746928334236145 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q418 |
| concepts[10].display_name | Telecommunications |
| concepts[11].id | https://openalex.org/C115961682 |
| concepts[11].level | 2 |
| concepts[11].score | 0.15647247433662415 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q860623 |
| concepts[11].display_name | Image (mathematics) |
| keywords[0].id | https://openalex.org/keywords/synthetic-aperture-radar |
| keywords[0].score | 0.6794730424880981 |
| keywords[0].display_name | Synthetic aperture radar |
| keywords[1].id | https://openalex.org/keywords/remote-sensing |
| keywords[1].score | 0.5147285461425781 |
| keywords[1].display_name | Remote sensing |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.4840192496776581 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/noise |
| keywords[3].score | 0.4833090305328369 |
| keywords[3].display_name | Noise (video) |
| keywords[4].id | https://openalex.org/keywords/interferometric-synthetic-aperture-radar |
| keywords[4].score | 0.4597412049770355 |
| keywords[4].display_name | Interferometric synthetic aperture radar |
| keywords[5].id | https://openalex.org/keywords/radar-imaging |
| keywords[5].score | 0.41196727752685547 |
| keywords[5].display_name | Radar imaging |
| keywords[6].id | https://openalex.org/keywords/environmental-science |
| keywords[6].score | 0.3660491406917572 |
| keywords[6].display_name | Environmental science |
| keywords[7].id | https://openalex.org/keywords/geology |
| keywords[7].score | 0.35789138078689575 |
| keywords[7].display_name | Geology |
| keywords[8].id | https://openalex.org/keywords/radar |
| keywords[8].score | 0.3454247713088989 |
| keywords[8].display_name | Radar |
| keywords[9].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[9].score | 0.3220348358154297 |
| keywords[9].display_name | Artificial intelligence |
| keywords[10].id | https://openalex.org/keywords/telecommunications |
| keywords[10].score | 0.17746928334236145 |
| keywords[10].display_name | Telecommunications |
| keywords[11].id | https://openalex.org/keywords/image |
| keywords[11].score | 0.15647247433662415 |
| keywords[11].display_name | Image (mathematics) |
| language | en |
| locations[0].id | doi:10.1080/23311916.2024.2359999 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S2764513175 |
| locations[0].source.issn | 2331-1916 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2331-1916 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Cogent Engineering |
| locations[0].source.host_organization | https://openalex.org/P4310311767 |
| locations[0].source.host_organization_name | Cogent OA |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310311767 |
| locations[0].source.host_organization_lineage_names | Cogent OA |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.tandfonline.com/doi/pdf/10.1080/23311916.2024.2359999?needAccess=true |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Cogent Engineering |
| locations[0].landing_page_url | https://doi.org/10.1080/23311916.2024.2359999 |
| locations[1].id | pmh:oai:doaj.org/article:d9f17346a2b0490a87cfd7bf0b9b5ba4 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306401280 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[1].source.host_organization | |
| locations[1].source.host_organization_name | |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | Cogent Engineering, Vol 11, Iss 1 (2024) |
| locations[1].landing_page_url | https://doaj.org/article/d9f17346a2b0490a87cfd7bf0b9b5ba4 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5009592180 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Ragesh Rajan M |
| authorships[0].countries | IN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I81556334 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of ECE, Amrita Vishwa Vidyapeetham, Kollam, Kerala, India |
| authorships[0].institutions[0].id | https://openalex.org/I81556334 |
| authorships[0].institutions[0].ror | https://ror.org/03am10p12 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I81556334 |
| authorships[0].institutions[0].country_code | IN |
| authorships[0].institutions[0].display_name | Amrita Vishwa Vidyapeetham |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Rajan M. Ragesh |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Department of ECE, Amrita Vishwa Vidyapeetham, Kollam, Kerala, India |
| authorships[1].author.id | https://openalex.org/A5014459721 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | M. Vinayababu |
| authorships[1].affiliations[0].raw_affiliation_string | Department of ECE, MES College of Engineering, Kuttippuram, Kerala, India |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | M. Vinayababu |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Department of ECE, MES College of Engineering, Kuttippuram, Kerala, India |
| authorships[2].author.id | https://openalex.org/A5000528488 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-1796-5995 |
| authorships[2].author.display_name | Shilpa Suresh |
| authorships[2].countries | IN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I164861460 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Mechatronics, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India |
| authorships[2].institutions[0].id | https://openalex.org/I164861460 |
| authorships[2].institutions[0].ror | https://ror.org/02xzytt36 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I164861460 |
| authorships[2].institutions[0].country_code | IN |
| authorships[2].institutions[0].display_name | Manipal Academy of Higher Education |
| authorships[2].author_position | last |
| authorships[2].raw_author_name | Suresh Shilpa |
| authorships[2].is_corresponding | True |
| authorships[2].raw_affiliation_strings | Department of Mechatronics, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India |
| has_content.pdf | True |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.tandfonline.com/doi/pdf/10.1080/23311916.2024.2359999?needAccess=true |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | A robust framework for removing G 0 distributed noise from Synthetic Aperture Radar images |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10801 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 0.9994999766349792 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2202 |
| primary_topic.subfield.display_name | Aerospace Engineering |
| primary_topic.display_name | Synthetic Aperture Radar (SAR) Applications and Techniques |
| related_works | https://openalex.org/W3206958763, https://openalex.org/W2159160885, https://openalex.org/W2148958581, https://openalex.org/W2545123933, https://openalex.org/W2585813813, https://openalex.org/W2042726296, https://openalex.org/W2096748030, https://openalex.org/W3016428515, https://openalex.org/W2160730947, https://openalex.org/W2747205507 |
| cited_by_count | 0 |
| locations_count | 2 |
| best_oa_location.id | doi:10.1080/23311916.2024.2359999 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S2764513175 |
| best_oa_location.source.issn | 2331-1916 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2331-1916 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Cogent Engineering |
| best_oa_location.source.host_organization | https://openalex.org/P4310311767 |
| best_oa_location.source.host_organization_name | Cogent OA |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310311767 |
| best_oa_location.source.host_organization_lineage_names | Cogent OA |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.tandfonline.com/doi/pdf/10.1080/23311916.2024.2359999?needAccess=true |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Cogent Engineering |
| best_oa_location.landing_page_url | https://doi.org/10.1080/23311916.2024.2359999 |
| primary_location.id | doi:10.1080/23311916.2024.2359999 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S2764513175 |
| primary_location.source.issn | 2331-1916 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2331-1916 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Cogent Engineering |
| primary_location.source.host_organization | https://openalex.org/P4310311767 |
| primary_location.source.host_organization_name | Cogent OA |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310311767 |
| primary_location.source.host_organization_lineage_names | Cogent OA |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.tandfonline.com/doi/pdf/10.1080/23311916.2024.2359999?needAccess=true |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Cogent Engineering |
| primary_location.landing_page_url | https://doi.org/10.1080/23311916.2024.2359999 |
| publication_date | 2024-06-05 |
| publication_year | 2024 |
| referenced_works | https://openalex.org/W2111326031, https://openalex.org/W2891999407, https://openalex.org/W2097073572, https://openalex.org/W1989854489, https://openalex.org/W2057260249, https://openalex.org/W2945177640, https://openalex.org/W2965472864, https://openalex.org/W1973657137, https://openalex.org/W4313503080, https://openalex.org/W6683219839, https://openalex.org/W56535966, https://openalex.org/W2117294245, https://openalex.org/W2076063977, https://openalex.org/W2423449433, https://openalex.org/W4220965003, https://openalex.org/W4362581794, https://openalex.org/W2018021323, https://openalex.org/W2125188192, https://openalex.org/W2470311561, https://openalex.org/W2013388817, https://openalex.org/W2114770744, https://openalex.org/W3162147927, https://openalex.org/W2954537798, https://openalex.org/W2057771708, https://openalex.org/W4288783052, https://openalex.org/W4205481278, https://openalex.org/W2023005931, https://openalex.org/W4213118873, https://openalex.org/W4213150710, https://openalex.org/W2170151025, https://openalex.org/W2079299474, https://openalex.org/W2966195154, https://openalex.org/W3112727310, https://openalex.org/W6635873946, https://openalex.org/W4207046083, https://openalex.org/W4389449578, https://openalex.org/W4384133683, https://openalex.org/W2062871215, https://openalex.org/W2325337530, https://openalex.org/W2404817793, https://openalex.org/W2147985697, https://openalex.org/W2914717758, https://openalex.org/W3127275778, https://openalex.org/W4308587699, https://openalex.org/W4309190560, https://openalex.org/W4248431698, https://openalex.org/W4327852082, https://openalex.org/W4212959628, https://openalex.org/W4281656111, https://openalex.org/W2133665775, https://openalex.org/W4321792289, https://openalex.org/W2133954466, https://openalex.org/W2290144871, https://openalex.org/W2961287872, https://openalex.org/W1602107991, https://openalex.org/W4247375313, https://openalex.org/W3151941575, https://openalex.org/W2799710450, https://openalex.org/W2155395881, https://openalex.org/W4300423820, https://openalex.org/W4226012892, https://openalex.org/W3113142645 |
| referenced_works_count | 62 |
| abstract_inverted_index.0 | 53 |
| abstract_inverted_index.G | 52 |
| abstract_inverted_index.a | 47, 172 |
| abstract_inverted_index.By | 97 |
| abstract_inverted_index.G0 | 167 |
| abstract_inverted_index.as | 166 |
| abstract_inverted_index.by | 117 |
| abstract_inverted_index.in | 30, 78, 85 |
| abstract_inverted_index.of | 39, 93, 114 |
| abstract_inverted_index.on | 151 |
| abstract_inverted_index.to | 75, 106 |
| abstract_inverted_index.SAR | 24, 33, 79, 88, 156, 161 |
| abstract_inverted_index.The | 43 |
| abstract_inverted_index.and | 16, 35, 68, 90, 101, 131, 140, 154 |
| abstract_inverted_index.for | 50, 121, 159, 176 |
| abstract_inverted_index.our | 169 |
| abstract_inverted_index.the | 27, 36, 72, 83, 91, 110, 145 |
| abstract_inverted_index.two | 20 |
| abstract_inverted_index.Edge | 141 |
| abstract_inverted_index.This | 62 |
| abstract_inverted_index.both | 152 |
| abstract_inverted_index.data | 162 |
| abstract_inverted_index.from | 56 |
| abstract_inverted_index.like | 134 |
| abstract_inverted_index.more | 173 |
| abstract_inverted_index.real | 155 |
| abstract_inverted_index.than | 178 |
| abstract_inverted_index.with | 163 |
| abstract_inverted_index.(SAR) | 3, 60 |
| abstract_inverted_index.(SFO) | 130 |
| abstract_inverted_index.Index | 137, 143 |
| abstract_inverted_index.Radar | 2, 59 |
| abstract_inverted_index.data. | 157 |
| abstract_inverted_index.finds | 5 |
| abstract_inverted_index.image | 25, 80 |
| abstract_inverted_index.noise | 55, 99, 108, 164 |
| abstract_inverted_index.study | 45, 111 |
| abstract_inverted_index.using | 127 |
| abstract_inverted_index.(EPI), | 144 |
| abstract_inverted_index.(SSIM) | 139 |
| abstract_inverted_index.across | 8 |
| abstract_inverted_index.domain | 74 |
| abstract_inverted_index.hinder | 23 |
| abstract_inverted_index.images | 34, 89 |
| abstract_inverted_index.impact | 38, 92 |
| abstract_inverted_index.linear | 115 |
| abstract_inverted_index.method | 147 |
| abstract_inverted_index.noise. | 42, 96 |
| abstract_inverted_index.robust | 48 |
| abstract_inverted_index.within | 71 |
| abstract_inverted_index.Bitonic | 65, 119 |
| abstract_inverted_index.Measure | 138 |
| abstract_inverted_index.Through | 124 |
| abstract_inverted_index.address | 76 |
| abstract_inverted_index.adverse | 37 |
| abstract_inverted_index.biomass | 14 |
| abstract_inverted_index.filters | 67, 116, 120 |
| abstract_inverted_index.imagery | 4 |
| abstract_inverted_index.images. | 61 |
| abstract_inverted_index.modeled | 165 |
| abstract_inverted_index.speckle | 41, 95 |
| abstract_inverted_index.wavelet | 73 |
| abstract_inverted_index.Aperture | 1, 58 |
| abstract_inverted_index.However, | 19 |
| abstract_inverted_index.SailFish | 69, 128 |
| abstract_inverted_index.adopting | 118 |
| abstract_inverted_index.applying | 102 |
| abstract_inverted_index.approach | 170 |
| abstract_inverted_index.existing | 179 |
| abstract_inverted_index.inherent | 28 |
| abstract_inverted_index.methods. | 180 |
| abstract_inverted_index.proposed | 44, 146 |
| abstract_inverted_index.provides | 171 |
| abstract_inverted_index.removing | 51 |
| abstract_inverted_index.surveys, | 13 |
| abstract_inverted_index.tailored | 105 |
| abstract_inverted_index.utilizes | 64 |
| abstract_inverted_index.visually | 31, 86 |
| abstract_inverted_index.Synthetic | 0, 57 |
| abstract_inverted_index.analysis, | 81 |
| abstract_inverted_index.analysis: | 26 |
| abstract_inverted_index.assessing | 98 |
| abstract_inverted_index.benchmark | 175 |
| abstract_inverted_index.denoising | 103 |
| abstract_inverted_index.effective | 122 |
| abstract_inverted_index.estimated | 107 |
| abstract_inverted_index.framework | 49, 63 |
| abstract_inverted_index.functions | 133 |
| abstract_inverted_index.objective | 132 |
| abstract_inverted_index.overcomes | 112 |
| abstract_inverted_index.parameter | 125 |
| abstract_inverted_index.realistic | 174 |
| abstract_inverted_index.synthetic | 153, 160 |
| abstract_inverted_index.Similarity | 136 |
| abstract_inverted_index.Structural | 135 |
| abstract_inverted_index.algorithms | 104, 150 |
| abstract_inverted_index.challenges | 22, 77 |
| abstract_inverted_index.comparison | 177 |
| abstract_inverted_index.difficulty | 29, 84 |
| abstract_inverted_index.introduces | 46 |
| abstract_inverted_index.vegetation | 12 |
| abstract_inverted_index.widespread | 6 |
| abstract_inverted_index.distributed | 54 |
| abstract_inverted_index.engineering | 9 |
| abstract_inverted_index.estimation, | 15 |
| abstract_inverted_index.limitations | 113 |
| abstract_inverted_index.outperforms | 148 |
| abstract_inverted_index.significant | 21 |
| abstract_inverted_index.Furthermore, | 158 |
| abstract_inverted_index.Optimization | 129 |
| abstract_inverted_index.Preservation | 142 |
| abstract_inverted_index.applications | 7 |
| abstract_inverted_index.conventional | 149 |
| abstract_inverted_index.disciplines, | 10 |
| abstract_inverted_index.distributed, | 168 |
| abstract_inverted_index.distribution | 100 |
| abstract_inverted_index.encompassing | 11 |
| abstract_inverted_index.interpreting | 32, 87 |
| abstract_inverted_index.optimization | 70, 126 |
| abstract_inverted_index.particularly | 82 |
| abstract_inverted_index.distribution, | 109 |
| abstract_inverted_index.preprocessing | 66 |
| abstract_inverted_index.multiplicative | 40, 94 |
| abstract_inverted_index.preprocessing. | 123 |
| abstract_inverted_index.investigations. | 18 |
| abstract_inverted_index.weather-related | 17 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5000528488 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| corresponding_institution_ids | https://openalex.org/I164861460 |
| citation_normalized_percentile.value | 0.04591716 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |