Comparing Pan-Sharpening Algorithms to Access an Agriculture Area: A Mississippi Case Study

Numerous satellites collect imagery of the Earth’s surface daily, providing information to public and private sectors. The fusion (pan-sharpening) high-resolution panchromatic satellite with lower-resolution multispectral has shown promise for monitoring natural resources farming areas. It results in new more detail than original or images. In agricultural areas Mississippi, landscapes can range from complex mixtures vegetation built-up dense vegetative regions. More is needed on pan-sharpened assessing rural Mississippi. WorldView 3 consisting commonly found Mississippi was subjected 17 pan-sharpening algorithms. images were compared qualitatively quantitatively three quality indices: 1) Erreur Relative Globale Addimensionelle de Synthese; 2) Universal Image Quality Index; 3) Bias. à trous wavelet transform injection model hyperspherical color spaced methods ranked among best maintaining image integrity qualitative quantitative analyses. optimized high-pass filter method often last by indices. smoothing filter-based intensity modulation algorithm gaussian transfer function match filtered added artifacts Pan-sharpened great potential enhance survey Mississippi’s key success selecting an process that increases spatial content while not compromising integrity.