satellite image pansharpening using a hybrid approach for object-based image analysis

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ID: 235765
2012
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Abstract
Intensity-Hue-Saturation (IHS), Brovey Transform (BT), and Smoothing-Filter-Based-Intensity Modulation (SFIM) algorithms were used to pansharpen GeoEye-1 imagery. The pansharpened images were then segmented in Berkeley Image Seg using a wide range of segmentation parameters, and the spatial and spectral accuracy of image segments was measured. We found that pansharpening algorithms that preserve more of the spatial information of the higher resolution panchromatic image band (i.e., IHS and BT) led to more spatially-accurate segmentations, while pansharpening algorithms that minimize the distortion of spectral information of the lower resolution multispectral image bands (i.e., SFIM) led to more spectrally-accurate image segments. Based on these findings, we developed a new IHS-SFIM combination approach, specifically for object-based image analysis (OBIA), which combined the better spatial information of IHS and the more accurate spectral information of SFIM to produce image segments with very high spatial and spectral accuracy.
Reference Key
hoan2012isprssatellite Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Nguyen Thanh Hoan;Ryutaro Tateishi;Brian Alan Johnson
Journal población y desarrollo
Year 2012
DOI
10.3390/ijgi1030228
URL
http://www.mdpi.com/2220-9964/1/3/228
Keywords
image segmentation obia geobia

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