Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 8 of 8 for “"Complex wavelets"”.
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Uses of Complex Wavelets in Deep Convolutional Neural Networks
… and many other tasks). In particular, we use complex wavelets (rather than the Fourier transform or the discrete wavelet transform) as basis functions to reformulate image understanding with deep networks. In this thesis, we explore the most popular and well-developed form of using complex …
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Development and evaluation of a multiscale keypoint detector based on complex wavelets
… detector and descriptor based on the Dual-Tree Complex Wavelet Transform (DTCWT). First, we develop a scale-space framework called the 4S-DTCWT that uses the dyadic decomposition of the DTCWT but achieves denser sampling in scale by interleaving several DTCWT trees, leading to reduced …
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Assessing self-similarity in redundant complex and quaternion wavelet domains: Theory and applications
… we propose spectral tools based on non-decimated complex wavelet transforms implemented by their matrix formulation. A structural redundancy in non-decimated wavelets and a componential redundancy in complex wavelets act in a synergy when extracting wavelet-based informative descriptors. Next, we …
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Low-complexity methods for image and video watermarking
… advantage of the properties of the dual-tree complex wavelet transform (DT CWT). This transform offers the advantages of both the regular and the complex wavelets (perfect reconstruction, approximate shift invariance and good directional selectivity). Our methods use these characteristics to …
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A neural relevance model for feature extraction from hyperspectral images, and its application in the wavelet domain
… Feature extraction models based on PCA or wavelets judge feature importance by the magnitude of the transform coefficients, rarely leading to an appropriate set of features for classification. We analyze a recent neural paradigm, Generalized Relevance Learning Vector Quantization (GRLVQ) …
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Improved detection and quantisation of keypoints in the complex wavelet domain
… categoriser (or quantiser). The Dual Tree Complex Wavelet Transform (DTCWT) decomposes an image into oriented subbands at a range of scales. The resulting domain is arguably well suited for further image analysis tasks such as feature identification. This thesis develops feature …