@inproceedings {262,
	title = {Remote sensing image synthesis},
	booktitle = {2010 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)},
	year = {2010},
	abstract = {<p>For remote sensing data, the testing analysis tools is difficult since the ground-truth data are not available in many cases. To address this issue, a novel method for image synthesis is presented for use as a evaluation test-bed. Given the scale-dependent, non-stationary nature of remotely sensed data, a new modeling approach that combines a resolution-oriented hierarchical method with a regional label-oriented binary tree structure is introduced to synthesize such complex data. In this paper, we are proposing on first synthesizing a label field, which contains the complex structural characteristics, then synthesizing the texture based on the generated label field for a more accurate modeling. Experimental results using operational RADARSAT SAR sea-ice image data show that the proposed method is capable of modeling complex, nonstationary scale structures, thus making it well-suitable to produce reliable, realistic remote sensing imagery.</p>
},
	keywords = {complex nonstationary scale structures, complex structural characteristics, evaluation test-bed, ground-truth data, image synthesis, label field, operational RADARSAT SAR sea-ice image data, radar imaging, regional label-oriented binary tree structure, remote sensing by radar, remote sensing data, remote sensing imagery, remotely sensed data, resolution-oriented hierarchical method, scale-dependent nonstationary nature, synthetic aperture radar, testing analysis tools},
	doi = {http://dx.doi.org/10.1109/IGARSS.2010.5649342},
	author = {Y Liu and A Wong and P Fieguth}
}
