期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2008
卷号：XXXVII Part B7
页码：1281-1286
出版社：Copernicus Publications
摘要：Merging of different data sets is often used in digital image processing to improve the visual and analytical quality of the data. The analyst may need to merge different types of data. In this process, different data such as satellite imagery from the same sensor but with different resolution, satellite imagery from different sensors with varying resolution, digitized aerial photography and satellite imagery or satellite imagery with ancillary information can be merged. In this paper, the efficiency of three different merging techniques (Principal Component, IHS, and Brovey Transform) is examined, in order to improve the spatial resolution of very high resolution aerial photographs (1:35.000 scale panchromatic) with the Landsat 7 ETM imagery. The aim was to get best enhanced merged aerial imagery for the visual interpretation. Because of the very big difference between the resolutions of sources, the techniques give very different results. The general conclusion is that when the original source imagery is used, Principal Component and Brovey Transform merging techniques should be preferred for such kind of imagery. Other methods were also tested to enhance the merge imagery, such as, merging the multispectral Landsat 7 ETM imagery with Landsat 7 ETM panchromatic imagery at first and merging this imagery with aerial photographs again with three different merging techniques afterwards. In another method, multispectral Landsat 7 ETM imagery was resampled to higher resolution imageries and then panchromatic aerial imagery was merged with this resampled image with three different merging techniques. In all approaches, Brovey Transform and Principal Component techniques serve well the purpose of increasing resolution of the low resolution images with the high resolution images. However, all methods should be tested in different areas by using multispectral and panchromatic images which were taken in different time frames to define the overall performances of these methods and merging techniques
