Exploitation of Elevation Data from IFSAR

IFSAR is a technique to generate high-resolution digital elevation model (DEM) based on the phase difference in SAR signals received by two spatially separated antennas (11). There are drawbacks in height maps derived

Exploitation of Elevation Data from IFSAR

Fig. 3. An IFSAR image.

from IFSAR data: The data are noisy and the spatial resolution is much inferior to that of visual data. The spatial resolution is further degraded by the noise removal step. Figure 3 shows a height map produced by a real IFSAR. A typical IFSAR elevation image is noisy and needs to be filtered before it can be reliably used. Also, there are regions with “no data” that result either from the fact that the original scene was not on a rectangular grid or from radar geometry effects, which cause some points not to be mapped. Interpolation and nonlinear filtering techniques are used to filter the elevation data.

Positioning ofIFSAR and visual data allows for the fusion ofclues from both sensors for target recognition. It is needed to overcome various difficulties resulting from the limitations of the sensor. For example, building detection requires the extraction and grouping of features such as lines, corners, and building tops to form buildings (12). The features extracted from visual data usually contain many unwanted spurious edges, lines, and so on that do not correspond to buildings. The grouping stage requires complex and computationally intensive operations. Further, the height of a building is typically estimated by extracting shadows and sun angle when available and is not reliable when the shadows are cast on adjacent buildings. Another drawback of methods based exclusively on visual data lies in their sensitivity to imaging conditions.

IFSAR elevation data can be used in conjunction with visual data to overcome the aforementioned dif­ficulties. Current IFSAR technology provides sufficient elevation resolution to discriminate building regions from surrounding clutter. These building regions are not well defined from a visual image when the buildings have the same intensity level as their surrounding background. Similarly, a building having different colors may be wrongly segmented into several buildings. IFSAR data are not affected by color variations in buildings and therefore are better for building detection.

Figure 4 shows a visual image and edges detected by the Canny operator for the area shown in Fig. 3. The top part of Fig. 4 shows a building with two different roof colors and roof structures on many buildings. Many spurious edges not corresponding to the building appear in the edge map shown on the bottom right of Fig. 4. Using the IFSAR elevation map shown in Fig. 3, buildings and ground regions are labeled using a two class

Exploitation of Elevation Data from IFSAR

Exploitation of Elevation Data from IFSAR

Fig. 4. Visual image and edges detected by the Canny operator.

classifier. The IFSAR and visual images are registered. Figure 5 shows the result of registration of a visual image and the segmented elevation image. Features corresponding to roads, parked cars, trees, and so on are suppressed from the visual images using the segmented buildings derived from the IFSAR image.

The locations and the directions of edges in the segmented image are estimated and are used to locate edges of buildings in the visual image. In the visual image, an edge pixel corresponding to each edge pixel in the registered height image is searched in the direction perpendicular to the estimated direction in the height

Exploitation of Elevation Data from IFSAR

Fig. 5. Buildings segmented from the IFSAR image overlaid to visual image.

image. If an edge is found within a small neighborhood, the edge pixel is accepted as a valid edge of a building. If such a pixel is not found in the neighborhood, the edge is not accepted. Figure 6 shows the refined edges obtained by searching in the neighborhoods of height edges. Most of building edges in the height image are found while the unwanted edges are removed.

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