An object-based image analysis approach based on independent segmentations

Geographic Object-Based Image Analysis (GEOBIA) makes it possible to exploit a number of new features in the remote sensing image classification process. Such possibility is brought by the introduction of a segmentation step in the analysis process. The new features refer to aggregated spectral pixel values, textural, morphological and topological features computed for the different image segments. The usual segmentation approach in GEOBIA works relies on a hierarchy of segmentations, each level related to a number of object classes that have similar sizes, i.e., are detectable in a similar scale. We, therefore, propose an approach founded on the assumption that if segmentations are not specialized for each object class, then many of the new segment features cannot be properly exploited in the classification process. The proposed approach relies on a specific rule to solve eventual spatial conflicts among different segmentations. Preliminary experimental results show that the proposed approach performed better that the usual one.