|Title||Remote sensing image synthesis|
|Publication Type||Conference Paper|
|Year of Publication||2010|
|Authors||Liu, Y., A. Wong, and P. Fieguth|
|Conference Name||2010 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)|
|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|
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.