Titlebook: Object-Based Image Analysis; Spatial Concepts for Thomas Blaschke (Prof.),Stefan Lang (Dr.),Geoffrey Book 20081st edition Springer-Verlag B

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Identifying benefits of pre-processing large area QuickBird imagery for object-based image analysisding the forest. The high complexity of the farmland, with extremely small structured parcels, demands analysis strategies that make use of image derivates obtained from cadastral maps as well as ground truth information. Finally, the classification result is compared to one based on the unprocessed

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A hybrid texture-based and region-based multi-scale image segmentation algorithmthod, complex statistical measures of texture had to be computed based on objects, however, and not on rectangular image regions. The approach was to compute grey level co-occurrence matrices for each image object and then to compute object-based statistical features. The Advanced Texture Heuristics

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Semi-automated forest stand delineation using wavelet based segmentation of very high resolution opt the creation of pure forest stands and to improve classification performance. A parcel/stand purity index was developed to evaluate stand purity and the expected mapping accuracy was estimated by defining a potential mapping accuracy measure. Results showed that wavelet based image segmentation out

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Quality assessment of segmentation results devoted to object-based classificationas more useful than the one based on mean object size. On the other hand, it was shown that object size improved class discrimination but this could deteriorate the boundary quality. The use of complementary discrepancy indices is therefore required in the case of frequent under-segmentation.

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Book 20081st editionrt- less, its emergence has provided a new critical bridge to spatial concepts applied in multiscale landscape analysis, Geographic Information Systems (GIS) and the synergy between image-objects and their radiometric char- teristics and analyses in Earth Observation data (EO).

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