Three dimensional shape modeling: segmentation, reconstruction and registration

Accounting for uncertainty in three-dimensional (3D) shapes is important in a large number of scientific and engineering areas, such as biometrics, biomedical imaging, and data mining. It is well known that 3D polar shaped objects can be represented by Fourier descriptors such as spherical harmonics and double Fourier series. However, the statistics of these spectral shape models have not been widely explored. This thesis studies several areas involved in 3D shape modeling, including random field models for statistical shape modeling, optimal shape filtering, parametric active contours for object segmentation and surface reconstruction. It also investigates multi-modal image registration with respect to tumor activity quantification. Spherical harmonic expansions over the unit sphere not only provide a low dimensional polarimetric parameterization of stochastic shape, but also correspond to the Karhunen-Lo´eve (K-L) expansion of any isotropic random field on the unit sphere. Spherical ...

Li, Jia — University of Michigan


WATERMARKING FOR 3D REPRESENTATIONS

In this thesis, a number of novel watermarking techniques for different 3D representations are presented. A novel watermarking method is proposed for the mono-view video, which might be interpreted as the basic implicit representation of 3D scenes. The proposed method solves the common flickering problem in the existing video watermarking schemes by means of adjusting the watermark strength with respect to temporal contrast thresholds of human visual system (HVS), which define the maximum invisible distortions in the temporal direction. The experimental results indicate that the proposed method gives better results in both objective and subjective measures, compared to some recognized methods in the literature. The watermarking techniques for the geometry and image based representations of 3D scenes, denoted as 3D watermarking, are examined and classified into three groups, as 3D-3D, 3D-2D and 2D-2D watermarking, in which the pair of symbols ...

Koz, Alper — Middle East Technical University, Department of Electrical and Electronics Engineering


Advanced Coding Technologies For Medical and Holographic Imaging: Algorithms, Implementations and Standardization

Medical and holographic imaging modalities produce large datasets that require efficient compression mechanisms for storage and transmission. This PhD dissertation proposes state-of-the-art technology extensions for JPEG coding standards to improve their performance in the aforementioned application domains. Modern hospitals rely heavily on volumetric images, such as produced by CT and MRI scanners. In fact, the completely digitized medical work flow, the improved imaging scanner technologies and the importance of volumetric image data sets have led to an exponentially increasing amount of data, raising the necessity for more efficient compression techniques with support for progressive quality and resolution scalability. For this type of imagery, a volumetric extension of the JPEG 2000 standard was created, called JP3D. In addition, improvements to JP3D, being alternative wavelet filters, directional wavelets and an intra-band prediction mode, were proposed and their applicability was evaluated. Holographic imaging, ...

Bruylants, Tim — Vrije Universiteit Brussel


Spatiotonal Adaptivity in Super-Resolution of under-sampled Image Sequences

This thesis concerns the use of spatial and tonal adaptivity in improving the resolution of aliased image sequences under scene or camera motion. Each of the five content chapters focuses on a different subtopic of super-resolution: image registration (chapter 2), image fusion (chapter 3 and 4), super-resolution restoration (chapter 5), and super-resolution synthesis (chapter 6). Chapter 2 derives the Cramer-Rao lower bound of image registration and shows that iterative gradient-based estimators achieve this performance limit. Chapter 3 presents an algorithm for image fusion of irregularly sampled and uncertain data using robust normalized convolution. The size and shape of the fusion kernel is adapted to local curvilinear structures in the image. Each data sample is assigned an intensity-related certainty value to limit the influence of outliers. Chapter 4 presents two fast implementations of the signal-adaptive bilateral filter. The xy-separable implementation filters ...

Pham, Tuan Q. — Delft University of Technology


Combining anatomical and spectral information to enhance MRSI resolution and quantification: Application to Multiple Sclerosis

Multiple sclerosis is a progressive autoimmune disease that a˙ects young adults. Magnetic resonance (MR) imaging has become an integral part in monitoring multiple sclerosis disease. Conventional MR imaging sequences such as fluid attenuated inversion recovery imaging have high spatial resolution, and can visualise the presence of focal white matter brain lesions in multiple sclerosis disease. Manual delineation of these lesions on conventional MR images is time consuming and su˙ers from intra and inter-rater variability. Among the advanced MR imaging techniques, MR spectroscopic imaging can o˙er complementary information on lesion characterisation compared to conventional MR images. However, MR spectroscopic images have low spatial resolution. Therefore, the aim of this thesis is to automatically segment multiple sclerosis lesions on conventional MR images and use the information from high-resolution conventional MR images to enhance the resolution of MR spectroscopic images. Automatic single time ...

Jain, Saurabh — KU Leuven


Progressive visualization of incomplete sonar-data sets: from sea-bottom interpolation and segmentation to geometry extraction

This thesis describes a visualization pipeline for sonar profiling data that show reflections of multiple sediments in the sea bottom and that cover huge survey areas with many gaps. Visualizing such data is not trivial, because they may be noisy and because data sets may be very large. The developed techniques are: (1) Quadtree interpolation for estimating new sediment reflections, at all gaps in the longitude-latitude plane. The quadtree is used for guiding the 3D interpolation process: gaps become small at low spatial resolutions, where they can be filled by interpolating between available reflections. In the interpolation, the reflection data are cross correlated in order to construct continuity of multiple, sloping reflections. (2) Segmentation and boundary refinement in an octree in order to detect sediments in the sonar data. In the refinement, coarse boundaries are reclassified by filtering the data ...

Loke, Robert Edward — Delft University of Technology


Second-Order Multidimensional Independent Component Analysis: Theory and Methods

Independent component analysis (ICA) and blind source separation (BSS) deal with extracting a number of mutually independent elements from a set of observed linear mixtures. Motivated by various applications, this work considers a more general and more flexible model: the sources can be partitioned into groups exhibiting dependence within a given group but independence between two different groups. We argue that this is tantamount to considering multidimensional components, as opposed to the standard ICA case which is restricted to one-dimensional components. In this work, we focus on second-order methods to separate statistically-independent multidimensional components from their linear instantaneous mixture. The purpose of this work is to provide theoretical answers to questions which so far have been discussed mainly in the empirical domain. Namely, we provide a closed-form expression for the figure of merit, the mean square error (MSE), for multidimensional ...

Lahat, Dana — Tel Aviv University


Mixed structural models for 3D audio in virtual environments

In the world of Information and communications technology (ICT), strategies for innovation and development are increasingly focusing on applications that require spatial representation and real-time interaction with and within 3D-media environments. One of the major challenges that such applications have to address is user-centricity, reflecting e.g. on developing complexity-hiding services so that people can personalize their own delivery of services. In these terms, multimodal interfaces represent a key factor for enabling an inclusive use of new technologies by everyone. In order to achieve this, multimodal realistic models that describe our environment are needed, and in particular models that accurately describe the acoustics of the environment and communication through the auditory modality are required. Examples of currently active research directions and application areas include 3DTV and future internet, 3D visual-sound scene coding, transmission and reconstruction and teleconferencing systems, to name but ...

Geronazzo, Michele — University of Padova


Bayesian Fusion of Multi-band Images: A Powerful Tool for Super-resolution

Hyperspectral (HS) imaging, which consists of acquiring a same scene in several hundreds of contiguous spectral bands (a three dimensional data cube), has opened a new range of relevant applications, such as target detection [MS02], classification [C.-03] and spectral unmixing [BDPD+12]. However, while HS sensors provide abundant spectral information, their spatial resolution is generally more limited. Thus, fusing the HS image with other highly resolved images of the same scene, such as multispectral (MS) or panchromatic (PAN) images is an interesting problem. The problem of fusing a high spectral and low spatial resolution image with an auxiliary image of higher spatial but lower spectral resolution, also known as multi-resolution image fusion, has been explored for many years [AMV+11]. From an application point of view, this problem is also important as motivated by recent national programs, e.g., the Japanese next-generation space-borne ...

Wei, Qi — University of Toulouse


Unsupervised and semi-supervised Non-negative Matrix Factorization methods for brain tumor segmentation using multi-parametric MRI data

Gliomas represent about 80% of all malignant primary brain tumors. Despite recent advancements in glioma research, patient outcome remains poor. The 5 year survival rate of the most common and most malignant subtype, i.e. glioblastoma, is about 5%. Magnetic resonance imaging (MRI) has become the imaging modality of choice in the management of brain tumor patients. Conventional MRI (cMRI) provides excellent soft tissue contrast without exposing the patient to potentially harmful ionizing radiation. Over the past decade, advanced MRI modalities, such as perfusion-weighted imaging (PWI), diffusion-weighted imaging (DWI) and magnetic resonance spectroscopic imaging (MRSI) have gained interest in the clinical field, and their added value regarding brain tumor diagnosis, treatment planning and follow-up has been recognized. Tumor segmentation involves the imaging-based delineation of a tumor and its subcompartments. In gliomas, segmentation plays an important role in treatment planning as well ...

Sauwen, Nicolas — KU Leuven


Pointwise shape-adaptive DCT image filtering and signal-dependent noise estimation

When an image is acquired by a digital imaging sensor, it is always degraded by some noise. This leads to two basic questions: What are the main characteristics of this noise? How to remove it? These questions in turn correspond to two key problems in signal processing: noise estimation and noise removal (so-called denoising). This thesis addresses both abovementioned problems and provides a number of original and effective contributions for their solution. The first part of the thesis introduces a novel image denoising algorithm based on the low-complexity Shape-Adaptive Discrete Cosine Transform (SA-DCT). By using spatially adaptive supports for the transform, the quality of the filtered image is high, with clean edges and without disturbing artifacts. We further present extensions of this approach to image deblurring, deringing and deblocking, as well as to color image filtering. For all these applications, ...

Foi, Alessandro — Tampere University of Technology


Audio Visual Speech Enhancement

This thesis presents a novel approach to speech enhancement by exploiting the bimodality of speech production and the correlation that exists between audio and visual speech information. An analysis into the correlation of a range of audio and visual features reveals significant correlation to exist between visual speech features and audio filterbank features. The amount of correlation was also found to be greater when the correlation is analysed with individual phonemes rather than across all phonemes. This led to building a Gaussian Mixture Model (GMM) that is capable of estimating filterbank features from visual features. Phoneme-specific GMMs gave lower filterbank estimation errors and a phoneme transcription is decoded using audio-visual Hidden Markov Model (HMM). Clean filterbank estimates along with mean noise estimates were then utilised to construct visually-derived Wiener filters that are able to enhance noisy speech. The mean noise ...

Almajai, Ibrahim — University of East Anglia


Toward sparse and geometry adapted video approximations

Video signals are sequences of natural images, where images are often modeled as piecewise-smooth signals. Hence, video can be seen as a 3D piecewise-smooth signal made of piecewise-smooth regions that move through time. Based on the piecewise-smooth model and on related theoretical work on rate-distortion performance of wavelet and oracle based coding schemes, one can better analyze the appropriate coding strategies that adaptive video codecs need to implement in order to be efficient. Efficient video representations for coding purposes require the use of adaptive signal decompositions able to capture appropriately the structure and redundancy appearing in video signals. Adaptivity needs to be such that it allows for proper modeling of signals in order to represent these with the lowest possible coding cost. Video is a very structured signal with high geometric content. This includes temporal geometry (normally represented by motion ...

Divorra Escoda, Oscar — EPFL / Signal Processing Institute


Multi-Sensor Integration for Indoor 3D Reconstruction

Outdoor maps and navigation information delivered by modern services and technologies like Google Maps and Garmin navigators have revolutionized the lifestyle of many people. Motivated by the desire for similar navigation systems for indoor usage from consumers, advertisers, emergency rescuers/responders, etc., many indoor environments such as shopping malls, museums, casinos, airports, transit stations, offices, and schools need to be mapped. Typically, the environment is first reconstructed by capturing many point clouds from various stations and defining their spatial relationships. Currently, there is a lack of an accurate, rigorous, and speedy method for relating point clouds in indoor, urban, satellite-denied environments. This thesis presents a novel and automatic way for fusing calibrated point clouds obtained using a terrestrial laser scanner and the Microsoft Kinect by integrating them with a low-cost inertial measurement unit. The developed system, titled the Scannect, is the ...

Chow, Jacky — University of Calgary


Adaptive filtering algorithms for acoustic echo cancellation and acoustic feedback control in speech communication applications

Multimedia consumer electronics are nowadays everywhere from teleconferencing, hands-free communications, in-car communications to smart TV applications and more. We are living in a world of telecommunication where ideal scenarios for implementing these applications are hard to find. Instead, practical implementations typically bring many problems associated to each real-life scenario. This thesis mainly focuses on two of these problems, namely, acoustic echo and acoustic feedback. On the one hand, acoustic echo cancellation (AEC) is widely used in mobile and hands-free telephony where the existence of echoes degrades the intelligibility and listening comfort. On the other hand, acoustic feedback limits the maximum amplification that can be applied in, e.g., in-car communications or in conferencing systems, before howling due to instability, appears. Even though AEC and acoustic feedback cancellation (AFC) are functional in many applications, there are still open issues. This means that ...

Gil-Cacho, Jose Manuel — KU Leuven

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