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<doi_batch_id>-22b9b34417bc6092a744262</doi_batch_id>
<timestamp>20220216012024217</timestamp>
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<journal_metadata>   <full_title>International Journal of Innovative Technology and Exploring Engineering</full_title>   <abbrev_title>IJITEE</abbrev_title>   <issn media_type='electronic'>22783075</issn>   <doi_data>     <doi>10.35940/ijitee</doi>     <resource>https://www.ijitee.org/</resource>   </doi_data> </journal_metadata> <journal_issue>  <publication_date media_type='online'>     <month>03</month>     <day>30</day>     <year>2021</year>   </publication_date>   <journal_volume>     <volume>10</volume>   </journal_volume>   <issue>5</issue> </journal_issue><!-- ============== --> <journal_article publication_type='full_text'>   <titles>     <title>Image Registration and Fusion using Moving Frame based Decomposition Framework Algorithm</title>   </titles>   <contributors>      <organization sequence='first' contributor_role='author'>Department of Computer Science and Engineering, PDA College of Vishveraya Technological University Kalaburagi.</organization>    <person_name sequence='first' contributor_role='author'>      <given_name>Pooja</given_name>      <surname>Aspalli</surname>    </person_name>    <person_name sequence='additional' contributor_role='author'>       <given_name>Dr. Prakash</given_name>       <surname>Pattan</surname>     </person_name>     <organization sequence='additional' contributor_role='author'>Department of Computer Science and Engineering, P.D.A. College of Engineering, Gulbarga, Karnataka, India.</organization>   </contributors>    <jats:abstract xml:lang='en'>         <jats:p>Image fusion is an important process in the medical image diagnostics methods. Fusing images by obtaining information from different source and different types of images(modals) called multi-modal image fusion. This paper implements an effective and fast spatial domain based multi-modal image fusion using moving frame based decomposition (MFDF)method. Images from two different modalities are taken and decomposed to texture and approximation components. Weight mapping strategy is applied along with the guide filtering to fuse the approximation components using the final map. Weight mapping using the guide filtering is used for the fusing the images from different modalities. MATLAB is used for algorithm implementation. The results obtained are comparatively competitive with the recent publication[11]. Multi modal image fusion thus implemented gives promising results, when compared to moving frame decomposition framework method. The size and the blurring variable of the guiding filter is optimized to obtain a better Structural Similarity Index Measurement (SSIM).</jats:p>     </jats:abstract>  <publication_date media_type='online'>     <month>03</month>     <day>30</day>     <year>2021</year>   </publication_date>   <pages>     <first_page>57</first_page>     <last_page>63</last_page>   </pages>   <crossmark>     <crossmark_version>CC BY-NC-ND 4.0</crossmark_version>     <crossmark_policy>10.35940/BEIESP.CrossMarkPolicy</crossmark_policy>     <crossmark_domains>       <crossmark_domain>          <domain>www.ijitee.org</domain>       </crossmark_domain>     </crossmark_domains>     <crossmark_domain_exclusive>true</crossmark_domain_exclusive>   </crossmark>   <doi_data>     <doi>10.35940/ijitee.E8669.0310521</doi>     <resource>https://www.ijitee.org/portfolio-item/E86690310521/</resource>   </doi_data> </journal_article>
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