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11 May 2007 Efficient structures for image decomposition using directional filter banks
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Image decomposition using directional filter banks is useful in discovering and extracting edge orientation cues for target detection in airborne surveillance images. Since images of interest are very large and the filtered images are not downsampled in the application of interest, conventional filtering can be computationally extremely demanding and there is a need to explore procedures to make the filtering efficient. In this paper a novel filter bank structure for directional filtering of images is proposed and its design described. The design is carried out by imposing structural constraints on the filters, which are implemented using a generalized notion of separable filtering. The structure uses one-dimensional (1-D) filters as building blocks, which are employed in novel configurations to obtain filters with narrow wedge-shaped passbands. Design procedures have been developed for constructing 16-band, 32-band, and 64- band partitions starting with either built-in or user-specified 1-D prototypes. Implementations of filters using the proposed method show significant improvement compared with conventional implementation, often more by an order of magnitude, which is also supported by a theoretical analysis of the filter complexity.
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Rashid Ansari, Darius Fennell, Ahmet Bagci, William Reynolds, Derrick Campbell, and Bradley Chambers "Efficient structures for image decomposition using directional filter banks", Proc. SPIE 6566, Automatic Target Recognition XVII, 65660Y (11 May 2007);

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