Pansharpening with multi-CAE: impact of patch size and overlapping pixels on spectral and spatial distortion
[...]the relationship between the original PAN image and its degraded version is utilized to reconstruct the high-resolution MS image; in addition, an intensity component of MS image, which is obtained using an adaptive intensity-hue-saturation (AIHS), is reconstructed by utilizing the aforementione...
Gespeichert in:
| Veröffentlicht in: | Telkomnika 2024-08, Vol.22 (4), p.985-994 |
|---|---|
| Hauptverfasser: | , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 994 |
|---|---|
| container_issue | 4 |
| container_start_page | 985 |
| container_title | Telkomnika |
| container_volume | 22 |
| creator | Smadi, Ahmad Al Abugabah, Ahed Alsmadi, Mutasem Khlail Alsanabani, Ala Mehmood, Atif Al-Smadi, Ahmad Mohammad |
| description | [...]the relationship between the original PAN image and its degraded version is utilized to reconstruct the high-resolution MS image; in addition, an intensity component of MS image, which is obtained using an adaptive intensity-hue-saturation (AIHS), is reconstructed by utilizing the aforementioned relationship. A wide variety of pansharpening studies have been introduced in the literature, which can be grouped into three groups [9]: i) component substitution (CS) [10], [11]; ii) multiresolution analysis (MRA) [12], [13]; and iii) sparse representation (SR) [14], [15] based methods. The MRA based-methods such as indusion [21], wavelet transform [22], and generalized Laplacian pyramid (MTF-GLP) approach [23] leverages the detailed map by computing the variance between the PAN image and its low-resolution counterpart via PAN image decomposition. CAEs CAEs are considered unsupervised learning of convolutional filters. [...]any input would be used to extract features once a CAE has been learned [34]. |
| doi_str_mv | 10.12928/telkomnika.v22i4.25856 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_3092408930</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3092408930</sourcerecordid><originalsourceid>FETCH-LOGICAL-c760-ff96817f8b9187f206272c150d603270ef4ee260c4a7bb89d3ee9e696746936f3</originalsourceid><addsrcrecordid>eNpFkFtLAzEQhYMoWGp_gwGft2aT3Vx8K6VeoKAPfQ_pbmLT7m5iktbLrzeuggPDzMM5c5gPgOsSzUssML9Nuju4frAHNT9hbKs5rnlNz8AEE4QLgQU5B5OSClLkRpdgFuMe5WII14JPQPeihrhTwevBDq_w3aYd7I9dssVysbqDtveqSdAZ6FVqdjDaLw3V0EJ30qFT3v-YvP3QXYRugNHrJgXVjZKYLTbvrY3JhWTdcAUujOqinv3NKdjcrzbLx2L9_PC0XKyLhlFUGCMoL5nhW1FyZjCimOGmrFFLEcEMaVNpjSlqKsW2Wy5aorXQVFBW5R-pIVNw83vWB_d21DHJvTuGISdKggSuEM8osor9qprgYgzaSB9sr8KnLJEc4cp_uHKEK0e45BtXx3H1</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3092408930</pqid></control><display><type>article</type><title>Pansharpening with multi-CAE: impact of patch size and overlapping pixels on spectral and spatial distortion</title><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Smadi, Ahmad Al ; Abugabah, Ahed ; Alsmadi, Mutasem Khlail ; Alsanabani, Ala ; Mehmood, Atif ; Al-Smadi, Ahmad Mohammad</creator><creatorcontrib>Smadi, Ahmad Al ; Abugabah, Ahed ; Alsmadi, Mutasem Khlail ; Alsanabani, Ala ; Mehmood, Atif ; Al-Smadi, Ahmad Mohammad</creatorcontrib><description>[...]the relationship between the original PAN image and its degraded version is utilized to reconstruct the high-resolution MS image; in addition, an intensity component of MS image, which is obtained using an adaptive intensity-hue-saturation (AIHS), is reconstructed by utilizing the aforementioned relationship. A wide variety of pansharpening studies have been introduced in the literature, which can be grouped into three groups [9]: i) component substitution (CS) [10], [11]; ii) multiresolution analysis (MRA) [12], [13]; and iii) sparse representation (SR) [14], [15] based methods. The MRA based-methods such as indusion [21], wavelet transform [22], and generalized Laplacian pyramid (MTF-GLP) approach [23] leverages the detailed map by computing the variance between the PAN image and its low-resolution counterpart via PAN image decomposition. CAEs CAEs are considered unsupervised learning of convolutional filters. [...]any input would be used to extract features once a CAE has been learned [34].</description><identifier>ISSN: 1693-6930</identifier><identifier>EISSN: 2302-9293</identifier><identifier>DOI: 10.12928/telkomnika.v22i4.25856</identifier><language>eng</language><publisher>Yogyakarta: Ahmad Dahlan University</publisher><subject>Datasets ; Decomposition ; Deep learning ; Dictionaries ; Image degradation ; Image filters ; Image reconstruction ; Image resolution ; Methods ; Multiresolution analysis ; Neural networks ; Remote sensing ; Satellites ; Saturation (color) ; Unsupervised learning ; Wavelet transforms</subject><ispartof>Telkomnika, 2024-08, Vol.22 (4), p.985-994</ispartof><rights>2024. This work is published under https://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids></links><search><creatorcontrib>Smadi, Ahmad Al</creatorcontrib><creatorcontrib>Abugabah, Ahed</creatorcontrib><creatorcontrib>Alsmadi, Mutasem Khlail</creatorcontrib><creatorcontrib>Alsanabani, Ala</creatorcontrib><creatorcontrib>Mehmood, Atif</creatorcontrib><creatorcontrib>Al-Smadi, Ahmad Mohammad</creatorcontrib><title>Pansharpening with multi-CAE: impact of patch size and overlapping pixels on spectral and spatial distortion</title><title>Telkomnika</title><description>[...]the relationship between the original PAN image and its degraded version is utilized to reconstruct the high-resolution MS image; in addition, an intensity component of MS image, which is obtained using an adaptive intensity-hue-saturation (AIHS), is reconstructed by utilizing the aforementioned relationship. A wide variety of pansharpening studies have been introduced in the literature, which can be grouped into three groups [9]: i) component substitution (CS) [10], [11]; ii) multiresolution analysis (MRA) [12], [13]; and iii) sparse representation (SR) [14], [15] based methods. The MRA based-methods such as indusion [21], wavelet transform [22], and generalized Laplacian pyramid (MTF-GLP) approach [23] leverages the detailed map by computing the variance between the PAN image and its low-resolution counterpart via PAN image decomposition. CAEs CAEs are considered unsupervised learning of convolutional filters. [...]any input would be used to extract features once a CAE has been learned [34].</description><subject>Datasets</subject><subject>Decomposition</subject><subject>Deep learning</subject><subject>Dictionaries</subject><subject>Image degradation</subject><subject>Image filters</subject><subject>Image reconstruction</subject><subject>Image resolution</subject><subject>Methods</subject><subject>Multiresolution analysis</subject><subject>Neural networks</subject><subject>Remote sensing</subject><subject>Satellites</subject><subject>Saturation (color)</subject><subject>Unsupervised learning</subject><subject>Wavelet transforms</subject><issn>1693-6930</issn><issn>2302-9293</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNpFkFtLAzEQhYMoWGp_gwGft2aT3Vx8K6VeoKAPfQ_pbmLT7m5iktbLrzeuggPDzMM5c5gPgOsSzUssML9Nuju4frAHNT9hbKs5rnlNz8AEE4QLgQU5B5OSClLkRpdgFuMe5WII14JPQPeihrhTwevBDq_w3aYd7I9dssVysbqDtveqSdAZ6FVqdjDaLw3V0EJ30qFT3v-YvP3QXYRugNHrJgXVjZKYLTbvrY3JhWTdcAUujOqinv3NKdjcrzbLx2L9_PC0XKyLhlFUGCMoL5nhW1FyZjCimOGmrFFLEcEMaVNpjSlqKsW2Wy5aorXQVFBW5R-pIVNw83vWB_d21DHJvTuGISdKggSuEM8osor9qprgYgzaSB9sr8KnLJEc4cp_uHKEK0e45BtXx3H1</recordid><startdate>20240801</startdate><enddate>20240801</enddate><creator>Smadi, Ahmad Al</creator><creator>Abugabah, Ahed</creator><creator>Alsmadi, Mutasem Khlail</creator><creator>Alsanabani, Ala</creator><creator>Mehmood, Atif</creator><creator>Al-Smadi, Ahmad Mohammad</creator><general>Ahmad Dahlan University</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BVBZV</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope></search><sort><creationdate>20240801</creationdate><title>Pansharpening with multi-CAE: impact of patch size and overlapping pixels on spectral and spatial distortion</title><author>Smadi, Ahmad Al ; Abugabah, Ahed ; Alsmadi, Mutasem Khlail ; Alsanabani, Ala ; Mehmood, Atif ; Al-Smadi, Ahmad Mohammad</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c760-ff96817f8b9187f206272c150d603270ef4ee260c4a7bb89d3ee9e696746936f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Datasets</topic><topic>Decomposition</topic><topic>Deep learning</topic><topic>Dictionaries</topic><topic>Image degradation</topic><topic>Image filters</topic><topic>Image reconstruction</topic><topic>Image resolution</topic><topic>Methods</topic><topic>Multiresolution analysis</topic><topic>Neural networks</topic><topic>Remote sensing</topic><topic>Satellites</topic><topic>Saturation (color)</topic><topic>Unsupervised learning</topic><topic>Wavelet transforms</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Smadi, Ahmad Al</creatorcontrib><creatorcontrib>Abugabah, Ahed</creatorcontrib><creatorcontrib>Alsmadi, Mutasem Khlail</creatorcontrib><creatorcontrib>Alsanabani, Ala</creatorcontrib><creatorcontrib>Mehmood, Atif</creatorcontrib><creatorcontrib>Al-Smadi, Ahmad Mohammad</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>East & South Asia Database</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Telkomnika</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Smadi, Ahmad Al</au><au>Abugabah, Ahed</au><au>Alsmadi, Mutasem Khlail</au><au>Alsanabani, Ala</au><au>Mehmood, Atif</au><au>Al-Smadi, Ahmad Mohammad</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Pansharpening with multi-CAE: impact of patch size and overlapping pixels on spectral and spatial distortion</atitle><jtitle>Telkomnika</jtitle><date>2024-08-01</date><risdate>2024</risdate><volume>22</volume><issue>4</issue><spage>985</spage><epage>994</epage><pages>985-994</pages><issn>1693-6930</issn><eissn>2302-9293</eissn><abstract>[...]the relationship between the original PAN image and its degraded version is utilized to reconstruct the high-resolution MS image; in addition, an intensity component of MS image, which is obtained using an adaptive intensity-hue-saturation (AIHS), is reconstructed by utilizing the aforementioned relationship. A wide variety of pansharpening studies have been introduced in the literature, which can be grouped into three groups [9]: i) component substitution (CS) [10], [11]; ii) multiresolution analysis (MRA) [12], [13]; and iii) sparse representation (SR) [14], [15] based methods. The MRA based-methods such as indusion [21], wavelet transform [22], and generalized Laplacian pyramid (MTF-GLP) approach [23] leverages the detailed map by computing the variance between the PAN image and its low-resolution counterpart via PAN image decomposition. CAEs CAEs are considered unsupervised learning of convolutional filters. [...]any input would be used to extract features once a CAE has been learned [34].</abstract><cop>Yogyakarta</cop><pub>Ahmad Dahlan University</pub><doi>10.12928/telkomnika.v22i4.25856</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1693-6930 |
| ispartof | Telkomnika, 2024-08, Vol.22 (4), p.985-994 |
| issn | 1693-6930 2302-9293 |
| language | eng |
| recordid | cdi_proquest_journals_3092408930 |
| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Datasets Decomposition Deep learning Dictionaries Image degradation Image filters Image reconstruction Image resolution Methods Multiresolution analysis Neural networks Remote sensing Satellites Saturation (color) Unsupervised learning Wavelet transforms |
| title | Pansharpening with multi-CAE: impact of patch size and overlapping pixels on spectral and spatial distortion |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-27T05%3A20%3A24IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Pansharpening%20with%20multi-CAE:%20impact%20of%20patch%20size%20and%20overlapping%20pixels%20on%20spectral%20and%20spatial%20distortion&rft.jtitle=Telkomnika&rft.au=Smadi,%20Ahmad%20Al&rft.date=2024-08-01&rft.volume=22&rft.issue=4&rft.spage=985&rft.epage=994&rft.pages=985-994&rft.issn=1693-6930&rft.eissn=2302-9293&rft_id=info:doi/10.12928/telkomnika.v22i4.25856&rft_dat=%3Cproquest_cross%3E3092408930%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3092408930&rft_id=info:pmid/&rfr_iscdi=true |