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|Title:||Automated Morphological Image Composition for Mosaicing Large Image Data Sets|
|Authors:||BIELSKI CONRAD; GRAZZINI JACOPO; SOILLE PIERRE|
|Citation:||Proceedings of the International Geoscience and Remote Sensing Symposium p. 4068-4071|
|JRC Publication N°:||JRC37670|
|Type:||Contributions to Conferences|
|Abstract:||Users of remotely sensed imagery are often faced with the need to stitch two or more overlapping scenes together. This is generally referred to as image composition and the outcome is a single image with no overlapping regions which is also called an image mosaic. The most difficult part of image composition however, is deciding where to place the cut line in overlapping regions. In the days of hardcopy remote sensing, technicians would cut pictures along salient image structures or features when creating mosaics in order to minimise the ability of visually detecting the cut lines. Recently, a morphological image compositing algorithm was proposed that is able to automatically delineate cut lines along salient image structures. This technique was developed specifically to deal with very large image data sets automatically and generates a visually appealing image mosaic. To minimise the visual detection of a cut line, the contrast should look natural and therefore cuts should not be made through image objects but rather along the object. This paper presents the algorithm behind the morphological image compositing technique and how it was applied to automatically generate a European wide image mosaic based on over 800 Landsat ETM+ scenes. A quantitative measure was developed in order to try and quantify the 'quality' of an automatically delineated seam line. The results demonstrate how invisible the delineated seam lines are to the human eye based on the morphological image compositing method but at the same time, the experiments show the difficulty of quantitatively determining the 'best' one.|
|JRC Institute:||Institute for Environment and Sustainability|
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