Influence of Image Fusion Approaches on Classification Accuracy – A Case Study
Colditz, Rene and Wehrmann, Thilo and Bachmann, Martin and Steinnocher, Klaus and Schmidt, Michael and Strunz, Guenter and Dech, Stefan (2006) Influence of Image Fusion Approaches on Classification Accuracy – A Case Study. International Journal of Remote Sensing, 27 (15), pp. 3311-3335. Taylor and Francis. DOI: 10.1080/01431160600649254. ISSN 0143-1161.
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While many studies in the field of image fusion of remotely sensed data aim towards deriving new algorithms for visual enhancement, there is little research on the influence of image fusion on other applications. One major application in earth science is land cover mapping. The concept of sensors with multiple spatial resolutions provides a potential for image fusion. It minimises errors of geometric alignment and atmospheric or temporal changes. This study focuses on the influence of image fusion on spectral classification algorithms and their accuracy. A Landsat 7 ETM+ image was used, where six multispectral bands (30 m) were fused with the corresponding 15m panchromatic channel. The fusion methods comprise rather common techniques like Brovey, hue-saturation-value transform, and principal component analysis, and more complex approaches, including adaptive image fusion, multisensor multiresolution image fusion technique, and wavelet transformation. Image classification was performed with supervised methods, e.g. maximum likelihood classifier, object-based classification, and support vector machines. The classification was assessed with test samples, a clump analysis, and techniques accounting for classification errors along land cover boundaries. It was found that the adaptive image fusion approach shows best results with low noise content. It resulted in a major improvement when compared with the reference, especially along object edges. Acceptable results were achieved by wavelet, multisensor multiresolution image fusion, and principal component analysis. Brovey and hue-saturationvalue image fusion performed poorly and cannot be recommended for classification of fused imagery.
|Title:||Influence of Image Fusion Approaches on Classification Accuracy – A Case Study|
|Date:||10 August 2006|
|Journal or Publication Title:||International Journal of Remote Sensing|
|In ISI Web of Science:||Yes|
|Page Range:||pp. 3311-3335|
|Publisher:||Taylor and Francis|
|Keywords:||Image fusion; Image analysis; Image classification; Classification accuracy; Land cover|
|HGF - Research field:||Aeronautics, Space and Transport|
|HGF - Program:||Space|
|HGF - Program Themes:||W EO - Erdbeobachtung|
|DLR - Research area:||Space|
|DLR - Program:||W EO - Erdbeobachtung|
|DLR - Research theme (Project):||W - Vorhaben Geowissenschaftl. Fernerkundungs- und GIS-Verfahren (old)|
|Institutes and Institutions:||German Remote Sensing Data Center > Environment and Security > Environment and Geoinformation|
|Deposited By:||Rene Colditz|
|Deposited On:||04 Sep 2006|
|Last Modified:||27 Apr 2009 13:03|
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