Satellite Image Pansharpening Using a Hybrid Approach for Object-Based Image Analysis

Brian Johnson,Nguyen Hoan,Ryutaro Tateishi

doi:10.3390/ijgi1030228

Brian Johnson, Nguyen Hoan + Show 1 more

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https://doi.org/10.3390/ijgi1030228

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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.

Highlights

Recent years have seen an increase in the number of satellites that acquire high spatial resolution imagery
Since IHS led to very spatially-accurate image segments and Smoothing-FilterBased-Intensity Modulation (SFIM) led to very spectrally-accurate image segments, we propose a new IHS-SFIM hybrid approach that combines the benefits of both pansharpening algorithms to produce a final segmented image with a high spatial and spectral accuracy
We compared the effects of IHS, Brovey Transform (BT), and SFIM pansharpening on the spatial and spectral accuracy of image segmentation and proposed a new IHS-SFIM hybrid approach based on the results of these comparisons

Summary

Introduction

Recent years have seen an increase in the number of satellites that acquire high spatial resolution imagery. The latest generation of these satellites (e.g., GeoEye-1, Worldview-2, Pléiades 1A) acquire imagery at a very high spatial resolution for a panchromatic (PAN) band (around 0.5 m) and at a slightly lower resolution (around 2 m) for several multispectral (MS) bands. For these types of remote sensing data that contain PAN and MS bands of different spatial resolutions, image fusion methods referred to as “pansharpening” methods are often performed to increase the resolution of the MS bands using the PAN band [1]. Some pansharpening methods incorporate an adjustable filter or parameter that allows users to control this tradeoff between color distortion and spatial resolution enhancement (e.g., [6,7,8,9,10])

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