Current techniques for building detection in Synthetic Aperture Radar (SAR) imagery can be computationally expensive and/or enforce stringent requirements for data acquisition. I present two techniques that are effective and efficient at determining an approximate building location. This approximate location can be used to extract a portion of the SAR image to then perform a more robust detection. The proposed techniques assume that for the desired image, bright lines and shadows (SAR artifact effects) are approximately labeled. These labels are enhanced and utilized to locate buildings, only if the related bright lines and shadows can be grouped. In order to find which of the bright lines and shadows are related, all of the bright lines are connected to all of the shadows. This allows the problem to be solved from a connected graph viewpoint, where the nodes are the bright lines and shadows and the arcs are the connections between bright lines and shadows. For the first technique (simple graph grouping), constraints based on angle of depression and the relationship between connected bright lines and shadows are applied to remove unrelated arcs. The second technique (weighted graph grouping) calculates weights for the connections and then performs a series of increasingly relaxed hard and soft thresholds. This thresholding results in groups of bright lines and shadows produced from various initial threshold levels. These different groups will be labeled and interpreted according to their initial thresholds. Once the related bright lines and shadows are grouped, their locations are combined to provide an approximate building location. Experimental results demonstrate the outcome of the two techniques. The two techniques are compared and discussed.
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