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- W37337657 abstract "Abstract : This project pursued a general theory for complex-valued multiscale signal and image modeling, processing, and analysis that is matched to singularity-rich data. Higher-dimensional signals that feature geometric manifold structures were of particular interest in developing theory and a practical toolset for analysis and processing. We pursued a three-pronged approach in creating new multiscale transforms, new geometric statistical models, and new manifold-based signal representations. The results of our research include (1) the Dual Tree Quaternion Wavelet, an efficient transform and analysis tool that features near shift invariance and linear computational complexity; (2) a geometric hidden Markov tree wavelet model, which accounts for geometric regularity by capturing the dependencies between complex wavelet coefficients along a contour; and (3) surflet representations of signal discontinuities with near optimal rate-distortion performance. These new tools have led to significant performance gains immediately applicable to a number of important Navy-relevant applications, including target detection and classification, image segmentation and fusion, and computer network traffic modeling." @default.
- W37337657 created "2016-06-24" @default.
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- W37337657 date "2010-02-10" @default.
- W37337657 modified "2023-09-25" @default.
- W37337657 title "Higher-Dimensional Signal Processing via Multiscale Geometric Analysis" @default.
- W37337657 doi "https://doi.org/10.21236/ada514181" @default.
- W37337657 hasPublicationYear "2010" @default.
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