Abstract
The high resolution remote sensing satellite Razaksat is a unique satellite system since it operates in a near-equatorial orbit with a low inclination angle of 9. In a first study scientists have found the images suitable for feature extraction in an urban context to update the road network at a scale of 1:25,000. In a preceding project for land cover mapping the research team used the five available bands of Razaksat imagery. This paper describes a continuation of the former study in which techniques are used to fuse the high resolution panchromatic band with the lower resolution multispectral bands. The study investigates the impact of pansharpening on the spatial and spectral content of the data. It compares various image fusion techniques and their impact on land use classification results. The image fusion techniques investigated are Brovey Transform, High Pass Filtering, Principal Component Analysis, Wavelet Approach and Ehlers Fusion. The images are classified using a maximum likelihood classifier. The results show that the use of an appropriate image fusion technique with adequately tuned parameters can improve quality of the resulting thematic maps.
Highlights
Optical remote sensing has its constraints in the humid tropics due to the frequent cloud cover in this region
Image fusion and pansharpening in particular has found its place in remote sensing image exploitation
Exploring existing fusion methods and evaluating land use classification accuracies that can be achieved this research aims at customizing the work flow for optimum information extraction from Razaksat images
Summary
Optical remote sensing has its constraints in the humid tropics due to the frequent cloud cover in this region. The study described in this paper focuses on value adding processing techniques to get the most out of the optical images. In the case of Razaksat providing high resolution panchromatic and multispectral image data single-sensor pansharpening can be performed. Exploring existing fusion methods and evaluating land use classification accuracies that can be achieved this research aims at customizing the work flow for optimum information extraction from Razaksat images. This paper describes part of a larger research project in the context of image fusion strategies. It concentrates on the suitability of different image fusion techniques for multispectral image classification. Section three introduces the issues in image fusion and the experiments conducted, followed by the land use classification performed. Series: Earth and Environmental Science 18 (2014) 012029 doi:10.1088/1755-1315/18/1/012029
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