  <?xml version="1.0"?>
<journal>
 <journal_metadata>
  <full_title>Fusion: Practice and Applications</full_title>
  <abbrev_title>FPA</abbrev_title>
  <issn media_type="print">2692-4048</issn>
  <issn media_type="electronic">2770-0070</issn>
  <doi_data>
   <doi>10.54216/FPA</doi>
   <resource>https://www.americaspg.com/journals/show/3926</resource>
  </doi_data>
 </journal_metadata>
 <journal_issue>
  <publication_date media_type="print">
   <year>2018</year>
  </publication_date>
  <publication_date media_type="online">
   <year>2018</year>
  </publication_date>
 </journal_issue>
 <journal_article publication_type="full_text">
  <titles>
   <title>Multiscale Feature Extraction for Remote Sensing Image Analysis Using Discrete Wavelet Transform</title>
  </titles>
  <contributors>
   <organization sequence="first" contributor_role="author">Ministry of Education, Wasit Education Directorate, Iraq</organization>
   <person_name sequence="first" contributor_role="author">
    <given_name>Oday</given_name>
    <surname>Oday</surname>
   </person_name>
   <organization sequence="first" contributor_role="author">University of Information Technology and Communications, Baghdad, Iraq</organization>
   <person_name sequence="additional" contributor_role="author">
    <given_name>Rajaa Daami</given_name>
    <surname>Resen</surname>
   </person_name>
   <organization sequence="first" contributor_role="author">University of Information Technology and Communications, Baghdad, Iraq</organization>
   <person_name sequence="additional" contributor_role="author">
    <given_name>Ali Nafea</given_name>
    <surname>Yousif</surname>
   </person_name>
   <organization sequence="first" contributor_role="author">Ministry of Education, Wasit Education Directorate, Iraq; Computer Department, College of Education for Pure Sciences, Wasit University, Iraq</organization>
   <person_name sequence="additional" contributor_role="author">
    <given_name>Oday Ali</given_name>
    <surname>Hassen</surname>
   </person_name>
   <organization sequence="first" contributor_role="author">University of Information Technology and Communications, Baghdad, Iraq</organization>
   <person_name sequence="additional" contributor_role="author">
    <given_name>Ansam A.</given_name>
    <surname>Abdulhussein</surname>
   </person_name>
  </contributors>
  <jats:abstract xml:lang="en">
   <jats:p>Remote sensing image evaluation faces continual challenges in extracting discriminative capabilities from complex; multi-scale landscapes the use of conventional spectral-spatial techniques, which often fail to capture hierarchical structures correctly. This examine proposes a brand-new methodology that leverages the discrete wavelet remodel (DWT) for multi-scale characteristic extraction. It is carried out thru Python and the PyWavelets library to offer an open-source, reproducible solution. The framework decomposes pictures into subscales of path and directional detail throughout multiple scales, extracting statistical and textural descriptors optimized for remote sensing obligations. A complete assessment of 500 multispectral patches (Sentinel-2, Landsat-8, and high-decision sensors) demonstrates advanced overall performance in land cover class, accomplishing an accuracy of 92.4%, outperforming uncooked pixel methods (84.1%), important issue evaluation (PCA) (87.3%), and GLCM-based totally techniques (89.6%). A sensitivity analysis famous that Daubeches wavelet 4 at decomposition level three improves function discriminability, in particular for agricultural textures (91.2% accuracy) and concrete limitations (IoU=0.873), while directional subbands (LHHL) reduce transition area mistakes by way of 23%. The computational efficiency (184 msmegapixel) remains possible. These consequences show that DWT is an effective and handy device for improving faraway sensing analysis, with the full code and datasets being made publicly available to promote community adoption and foster innovation.</jats:p>
  </jats:abstract>
  <publication_date media_type="print">
   <year>2026</year>
  </publication_date>
  <publication_date media_type="online">
   <year>2026</year>
  </publication_date>
  <pages>
   <first_page>142</first_page>
   <last_page>154</last_page>
  </pages>
  <doi_data>
   <doi>10.54216/FPA.210110</doi>
   <resource>https://www.americaspg.com/articleinfo/3/show/3926</resource>
  </doi_data>
 </journal_article>
</journal>
