Martino Pesaresi

TL;DR: The proposed method performs well in the presence of both low radiometric contrast and relatively low spatial resolution, which may produce a textural effect, a border effect, and ambiguity in the object/background distinction.

TL;DR: It is seen that relatively few features are needed to achieve the same classification accuracies as in the original feature space when classification of panchromatic high-resolution data from urban areas using morphological and neural approaches.

TL;DR: A new fully automatic image information extraction, generalization and mosaic workflow is presented that is based on multiscale textural and morphological image features extraction and a new systematic approach for quality control and validation allowing global spatial and thematic consistency checking is proposed and applied.

TL;DR: The technical achievements of Google Earth, and the functionality of this first generation of virtual globes, are reviewed against the Gore vision, to prompt a reexamination of the initial vision of Digital Earth.

TL;DR: It is shown that self-dual or even self-complementary filters are required in many applications to produce results independent of the local contrast of the searched image structures, and important issues overlooked in the past are addressed.