Efficient structures for image decomposition using directional filter banks

Ansari, Rashid; Fennell, Darius; Bagci, Ahmet; Reynolds, W. D.; Campbell, Derrick S.; Chambers, Bradley

doi:10.1117/12.720984

Cited by 2 publications

(1 citation statement)

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“…The custom filters are additional filters that have been designed in house using efficient directional filter bank decomposition techniques. 17 In each of the figures, a three level pyramid was used with 4, 8, and 16 directional bands generated at each level, from coarse to fine, respectively, using the vk filter. The denoising coefficients k 1 and k 2 were set to 2.25.…”

Section: Resultsmentioning

confidence: 99%

Wavelet-based target detection using multiscale directional analysis

et al. 2007

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Efficient processing of imagery derived from remote sensing systems has become ever more important due to increasing data sizes, rates, and bit depths. This paper proposes a target detection method that uses a special class of wavelets based on highly frequency-selective directional filter banks. The approach helps isolate object features in different directional filter output components. These components lend themselves well to the application of powerful denoising and edge detection procedures in the wavelet domain. Edge information is derived from directional wavelet decompositions to detect targets of known dimension in electro optical imagery. Results of successful detection of objects using the proposed method are presented in the paper. The approach highlights many of the benefits of working with directional wavelet analysis for image denoising and detection.

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Section: Resultsmentioning

confidence: 99%