Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
IGARSS_PPT_20110726.ppt
1. Xu Huaping, Wang Wei , Liu Xianghua Beihang University, China
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11. Fig.4 SAR image from TerraSAR-X Fig.5 Optical image from Quickbird Fig.6 Classification result of Fig.5 Fig.7 The result of Fig.4 Fig.8 The result of Fig.4 and Fig.5 Fig.9 The result of Fig.4 and Fig.5 with the fast annealing strategy
12. Evaluation of Results Segmentation results Pixel number of wrong segmentation Consuming time (s) Fig.7 1191 9.469 Fig.8 538 4.250 Fig.9 339 1.985
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Editor's Notes
Objection: to get better performance and faster process.
Minimum the energy. P(y) is constant given the image.
The essential idea of MRF model is that the label value of each pixel only interacts with that of its neighboring pixels and is independent from rest pixels of the image. Taking the segmentation label filed as a MRF is reasonable because the labels of most pixels are only influenced by their neighboring labels Where is the energy function of cliques. Is the partition function and is a constant for normalization. Generally, the multi-level logistic model is used, of which the potential function of pair-site cliques is defined as:
Two main steps are included: First, pixels of the optical image are classified into three classes: certain target pixels, certain background pixels and uncertain pixels. Second, the uncertain pixels are segmented by the simulated annealing algorithm with the fast annealing strategy while the certain pixels keep their labels marked by the optical image segmentation.
Where, and are target and background region, respectively. is the pixel value of the optical image in pixel . is the number of pixels included in and is the number of pixels included in . and are used as thresholds for classification of the optical image.
Where is the number of pixels with label in the neighborhood of pixel , is the number of pixels included in .
The method can be also used to multi-classes segmentation
![[object Object],[object Object],[object Object],[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)