Paper Info
Title
Satellite Image Pansharpening Using a Hybrid Approach for Object-Based Image Analysis.
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.
Year
DOI
Venue
2012
10.3390/ijgi1030228
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
Keywords
Field
DocType
pansharpening,image segmentation,object-based image analysis,image segmentation evaluation,GEOBIA,OBIA,GeoEye-1,high resolution imagery
Spatial analysis,Computer vision,Pattern recognition,Panchromatic film,Image texture,Segmentation,Multispectral image,Image segmentation,Artificial intelligence,Distortion,Geography,Satellite image
Journal
Volume
Issue
ISSN
1
3
2220-9964
Citations 
PageRank 
References 
5
0.62
10
Authors
3
Name
Order
Citations
PageRank
Brian Johnson1658.83
Ryutaro Tateishi27813.21
Hoan Nguyen Thanh3172.71