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Abstract
Subtractive resolution merge (SRM) is a contemporary image fusion method that produces highly preserved spatial and spectral resolution. This method is limited to dual sensor platforms with specific band ratios between the high-resolution panchromatic image (HRPI) and the low-resolution multispectral image (LRMI). An additional problem with SRM is that some bands are over- or under-represented due to the normalisation function applied. This article provides two modifications that resolve these limitations. SRM builds a synthetic low-resolution panchromatic image (LRPISYN) from the weighted sum of the LRMI bands. This image is modified by using a spatially resampled HRPI instead. The second modification is the use of a contrast and luminance index for the normalising function. These two modifications are tested on QuickBird images (multispectral and panchromatic), as well as fusing SPOT-5 (Satellite Pour l'Observation de la Terre) multispectral image and an aerial photograph. The results show improved quantitative metrics and unsupervised classification compared with the standard SRM technique and other contemporary image fusion methods. Both of these modifications are grouped into a patent pending technique that is called contrast and luminance normalised fusion.
Acknowledgements
We thank Foundation for Research, Science and Technology funded Outcome Based Investment (FRST OBI). contract UOWX0505 and Environment Waikato for providing resources for this work, as well as Dr. Kevin Collier for his technical support. Landcare Research Ltd. and Terralink International Ltd. are also acknowledged for orthorectifying SPOT and aerial photographs, respectively. GNS Science is acknowledged for its support to perform analysis using ENVI software.