文档介绍：Complex Wavelet Based
Image Analysis and Synthesis
This dissertation is submitted for the degree of Doctor of Philosophy
Peter de Rivaz Trinity College October 2000
University of Cambridge Department of Engineering
de Rivaz, Peter F. C. PhD thesis, University of Cambridge, October 2000.
Complex Wavelet Based Image Analysis and Synthesis
Key Words
Complex wavelets, multi-scale, texture segmentation, texture synthesis, in-
terpolation, deconvolution.
Copyright c . de Rivaz, 2000.
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. de Rivaz
Signal Processing munications Laboratory
Department of Engineering
Trumpington Street
Cambridge, CB2 1PZ, .
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Summary
This dissertation investigates the use plex wavelets in image processing.
The limitations of standard real wavelet methods are explained with emphasis on the
problem of shift dependence.
Complex wavelets can be used for both Bayesian and non-Bayesian processing. The
complex wavelets are first used to perform some non-Bayesian processing. We describe
how to extract features to characterise textured images and test this characterisation
by resynthesizing textures with matching features. We use these features for image
segmentation and show how it is possible to extend the feature set to model longer-
range correlations in images for better texture synthesis.
Second we describe a number of image models from within mon Bayesian frame-
work. This framework reveals the theoretical relations between wavelet and alternative
methods. We plex