Thesis (Ph. D.)--University of Missouri-Columbia, 1998. / Typescript. Vita. Includes bibliographical references (leaves 85-87). Also available on the Internet.

published_or_final_version / abstract / toc / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / abstract / toc / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / Mathematics / Master / Master of Philosophy

Η παρούσα διατριβή πραγματεύεται τον σχεδιασμό, την ανάπτυξη και υλοποίηση νέων μεθόδων επεξεργασίας εικόνας βασισμένες στον μετασχηματισμό μικροκυματιδίων (Wavelet Transform) με σκοπό την αφαίρεση θορύβου και την τμηματοποίηση των όζων καθώς και ανάλυσης εικόνας με σκοπό την αυτόματη ταξινόμηση των όζων σε όζους υψηλού και χαμηλού κινδύνου. / The aim of the present thesis was the design and implementation of new image processing and analysis methods in ultrasound thyroid images. The research procedure comprised two main concepts towards optimization of thyroid ultrasonography. The design and implementation of wavelet-based image processing methods towards speckle suppression and thyroid nodule segmentation and image analysis methods in order to evaluate the thyroid nodules malignancy risk factor.

No description available.

With the development of Geographical Information System (GIS) and remote sensing techniques, a great deal of data has provided a set of continuous samples of the earth surface from local, regional to global scales. Several multi-scale, multi-resolution, pyramid or hierarchical methods and statistical methods have been developed and used to investigate the scaling property of remotely sensed data: local variance, texture method, scale variance, semivariogram, and fractal analysis. This research introduces the wavelet transform into the realm of scale study in remote sensing and answers three research questions. Three specific objectives corresponding to the three research questions are answered. They include: (1) exploration of wavelets for scale-dependent analysis of remotely sensed imagery; (2) examination of the relationships between wavelet coefficients and classification accuracy for different resolutions and their improvement of classification accuracy; and (3) multiscaling analysis and stochastic down-scaling of an image by using the wavelet transform and multifractals. The significant results obtained are: (1) Haar wavelets can be used to investigate the scale-dependent and spatial structure of an image and provides another method for selection of optimal sampling size; (2) there is a good relationship between classification accuracy and wavelet coefficients. High/low wavelet coefficient reflects low/high classification accuracy in each land cover type. (3) the maximum likelihood classifier with inclusion of wavelet coefficients can improve land cover classification accuracies. (4) the moment-scale analysis of wavelet coefficients can be used to investigate the multifractal properties of an image. Also the stochastic down-scaling model developed based on wavelet and multifractal generates good simulation results of the fine resolution image.

No description available.

This thesis present a new algorithm for creating high quality surfaces from large data sets of oriented points, sampled using a laser range scanner. This method works in two phases. In the first phase, using wavelet surface reconstruction method, we calculate a rough estimate of the surface in the form of Haar wavelet coefficients, stored in an Octree. In the second phase, we modify these coefficients to obtain a higher quality surface. We cast this method as a gradient minimization problem in the wavelet domain. We show that the solution to the gradient minimization problem, in the wavelet domain, is a sparse linear system with dimensionality roughly proportional to the surface of the model in question. We introduce a fast inplace method, which uses various properties of Haar wavelets, to solve the linear system and demonstrate the results of the algorithm.

Proefschrift Universiteit van Amsterdam. / Met index, lit. opg. - Met samenvatting in het Nederlands.