In this thesis, novel progressive scalable region-of-interest (ROI) image coding schemes with rate-distortion-complexity trade-off based on residual vector quantization (RVQ) and matching pursuit (MP) are developed. RVQ and MP provide the encoder with multi-resolution signal analysis tools, which are useful for rate-distortion trade-off and can be used to render a selected region of an image with a specific quality. An image quality refinement strategy is presented in this thesis, which improves the quality of the ROI in a progressive manner. The reconstructed image can mimic foveated images in perceptual image coding context. The systems are unbalanced in the sense that the decoders have less computational requirements than the encoders. The methods also provide interactive way of information refinement for regions of image with receiver 's higher priority. The receiver is free to select multiple regions of interest and change his/her mind and choose alternative regions in the middle of signal transmission. The proposed RVQ and MP based image coding methods in this thesis raise a couple of issues and reveal some capabilities in image coding and communication. In RVQ based image coding, the effects of dictionary size, number of RVQ stages and the size of image blocks on the reconstructed image quality, the resulting bit rate, and the computational complexity are investigated. The progressive nature of the resulting bit-stream makes RVQ and MP based image coding methods suitable platforms for unequal error protection. Researchers have paid lots of attention to joint source-channel ( JSC) coding in recent years. In this popular framework, JSC decoding based on residual redundancy exploitation of a source coder output bit-stream is an interesting bandwidth efficient approach for signal reconstruction. In this thesis, we also addressed JSC decoding and error concealment problem for matching pursuit based coded images transmitted over a noisy memoryless channel. The problem is solved on minimum mean squared error (MMSE) estimation foundation and a suboptimal solution is devised, which yields high quality error concealment with different levels of computational complexity. The proposed decoding and error concealment solution takes advantage of the residual redundancy, which exists in neighboring image blocks as well as neighboring MP analysis stages, to improve the quality of the images with no increase in the required bandwidth. The effects of different parameters such as MP dictionary size and number of analysis stages on the performance of the proposed soft decoding method have also been investigated. / Thesis / Doctor of Philosophy (PhD)

In a wireless and mobile communication paradigm, distribution and sharing of video content often occurs over unfriendly network environments constrained by lack of sufficient bandwidth, and prone to jitter, delay and packet losses. The research presented in this thesis proposed an assortment of application-specific optimizations designed to enable high-quality video communication over bandwidth constrained and unreliable channels. This assortment of solutions, termed herein as the Application Specific Video Coding and Delivery (ASVCD) toolkit, comprises of content and network adaptive approaches such as Region of Interest (ROI) video coding, Multiple Representation Coding (MRC), and Multiple Representation Coding of the Region of Interest (ROI + MRC). Thus, the effectiveness of ROI based video-coding in facilitating diagnostically lossless delivery of surgical videos over very low bandwidth channels was studied in this thesis. Furthermore, to facilitate error resilient video delivery over channels prone to burst losses and signal loss intervals, the MRC scheme was presented in this thesis. Finally, the thesis proposed a scheme for unequal protection of the ROI in the video by using the MRC scheme to effectively enable a distance learning application. To summarize, the ASVCD toolkit contributed in enabling high-quality video communications applications to become seamless and pervasive.

This thesis addresses authenticity and integrity of medical images using watermarking. Hospital Information Systems (HIS), Radiology Information Systems (RIS) and Picture Archiving and Communication Systems (P ACS) now form the information infrastructure for today's healthcare as these provide new ways to store, access and distribute medical data that also involve some security risk. Watermarking can be seen as an additional tool for security measures. As the medical tradition is very strict with the quality of biomedical images, the watermarking method must be reversible or if not, region of Interest (ROI) needs to be defined and left intact. Watermarking should also serve as an integrity control and should be able to authenticate the medical image. Three watermarking techniques were proposed. First, Strict Authentication Watermarking (SAW) embeds the digital signature of the image in the ROI and the image can be reverted back to its original value bit by bit if required. Second, Strict Authentication Watermarking with JPEG Compression (SAW-JPEG) uses the same principal as SAW, but is able to survive some degree of JPEG compression. Third, Authentication Watermarking with Tamper Detection and Recovery (AW-TDR) is able to localise tampering, whilst simultaneously reconstructing the original image.

Transmission of medical images, that mandate lossless transmission of content over WLANs, presents a great challenge. The large size of these images coupled with the low acceptance of traditional image compression techniques within the medical community compounds the problem even more. These factors are of enormous significance in a hospital setting in the context of real-time image collaboration. However, recent advances in medical image compression techniques such as diagnostically lossless compression methodology, has made the solution to this difficult problem feasible. The growing popularity of high speed wireless LAN in enterprise applications and the introduction of the new 802.11n draft standard have made this problem pertinent. The thesis makes recommendations on the degree of compression to be performed for specific instances of image communication applications based on the image size and the underlying network devices and their topology. During our analysis, it was found that for most cases, only a portion of the image; typically the region of interest of the image will be able to meet the time deadline requirement. This dictates a need for adaptive method for maximizing the percentage of the image delivered to the receiver within the deadline. The problem of maximizing delivery of regions of interest of image data within the deadline has been effectively modeled as a multi-commodity flow problem in this work. Though this model provides an optimal solution to the problem, it is NP hard in computational complexity and hence cannot be implemented in dynamic networks. An approximation algorithm that uses greedy approach to flow allocation is proposed to cater to the connection requests in real time. While implementing integer programming model is not feasible due to time constraints, the heuristic can be used to provide a near-optimal solution for the problem of maximizing the reliable delivery of regions of interest of medical images within delay deadlines. This scenario may typically be expected when new connection requests are placed after the initial flow allocations have been made.

Importance prioritised coding is a principle aimed at improving the interpretability (or image content recognition) versus bit-rate performance of image coding systems. This can be achieved by (1) detecting and tracking image content or regions of interest (ROI) that are crucial to the interpretation of an image, and (2)compressing them in such a manner that enables ROIs to be encoded with higher fidelity and prioritised for dissemination or transmission. Traditional image coding systems prioritise image data according to an objective measure of distortion and this measure does not correlate well with image quality or interpretability. Importance prioritised coding, on the other hand, aims to prioritise image contents according to an 'importance map', which provides a means for modelling and quantifying the relative importance of parts of an image. In such a coding scheme the importance in parts of an image containing ROIs would be higher than other parts of the image. The encoding and prioritisation of ROIs means that the interpretability in these regions would be improved at low bit-rates. An importance prioritised image coder incorporated within the JPEG 2000 international standard for image coding, called IMP-J2K, is proposed to encode and prioritise ROIs according to an 'importance map'. The map can be automatically generated using image processing algorithms that result in a limited number of ROIs, or manually constructed by hand-marking OIs using a priori knowledge. The proposed importance prioritised coder coder provides a user of the encoder with great flexibility in defining single or multiple ROIs with arbitrary degrees of importance and prioritising them using IMP-J2K. Furthermore, IMP-J2K codestreams can be reconstructed by generic JPEG 2000 decoders, which is important for interoperability between imaging systems and processes. The interpretability performance of IMP-J2K was quantitatively assessed using the subjective National Imagery Interpretability Rating Scale (NIIRS). The effect of importance prioritisation on image interpretability was investigated, and a methodology to relate the NIIRS ratings, ROI importance scores and bit-rates was proposed to facilitate NIIRS specifications for importance prioritised coding. In addition, a technique is proposed to construct an importance map by allowing a user of the encoder to use gaze patterns to automatically determine and assign importance to fixated regions (or ROIs) in an image. The importance map can be used by IMP-J2K to bias the encoding of the image to these ROIs, and subsequently to allow a user at the receiver to reconstruct the image as desired by the user of the encoder. Ultimately, with the advancement of automated importance mapping techniques that can reliably predict regions of visual attention, IMP-J2K may play a significant role in matching an image coding scheme to the human visual system.

En imagerie nucléaire (scintigraphie, TEMP, TEP), les diagnostics sont fréquemment faits à l'aide des courbes d'activité temporelles des différents organes et tissus étudiés. Ces courbes représentent l'évolution de la distribution d'un traceur radioactif injecté dans le patient. Leur obtention est compliquée par la superposition des organes et des tissus dans les séquences d'images 2D, et il convient donc de séparer les différentes contributions présentes dans les pixels. Le problème de séparation de sources sous-jacent étant sous-déterminé, nous proposons d'y faire face dans cette thèse en exploitant différentes connaissances a priori d'ordre spatial et temporel sur les sources. Les principales connaissances intégrées ici sont les régions d'intérêt (ROI) des sources qui apportent des informations spatiales riches. Contrairement aux travaux antérieurs qui ont une approche binaire, nous intégrons cette connaissance de manière robuste à la méthode de séparation, afin que cette dernière ne soit pas sensible aux variations inter et intra-utilisateurs dans la sélection des ROI. La méthode de séparation générique proposée prend la forme d'une fonctionnelle à minimiser, constituée d'un terme d'attache aux données ainsi que de pénalisations et de relâchements de contraintes exprimant les connaissances a priori. L'étude sur des images de synthèse montrent les bons résultats de notre approche par rapport à l'état de l'art. Deux applications, l'une sur les reins, l'autre sur le cœur illustrent les résultats sur des données cliniques réelles. / In nuclear imaging (scintigraphy, SPECT, PET), diagnostics are often made with time activity curves (TAC) of organs and tissues. These TACs represent the dynamic evolution of tracer distribution inside patient's body. Extraction of TACs can be complicated by overlapping in the 2D image sequences, hence source separation methods must be used in order to extract TAC properly. However, the underlying separation problem is underdetermined. We propose to overcome this difficulty by adding some spatial and temporal prior knowledge about sources on the separation process. The main knowledge used in this work is region of interest (ROI) of organs and tissues. Unlike state of the art methods, ROI are integrated in a robust way in our method, in order to face user-dependancy in their selection. The proposed method is generic and minimize an objective function composed with a data fidelity criterion, penalizations and relaxations expressing prior knowledge. Results on synthetic datasets show the efficiency of the proposed method compare to state of the art methods. Two clinical applications on the kidney and on the heart are also adressed.

Made available in DSpace on 2016-03-15T19:37:51Z (GMT). No. of bitstreams: 1 Andre Brasiliano da Silva.pdf: 4815626 bytes, checksum: e53fa837ff6a7eb3cff0f55f4b3b26ac (MD5) Previous issue date: 2014-08-21 / Eye tracking is an important issue for Human Computer interaction, mainly for users with hand-eye coordination problems. The work presented here shows a low cost and robust eye tracking system capable to work with an HD stream. The implementations used in this work over the base system present diferent techniques in all stages, from face detection to iris detection. Local processing is used in most stages in this implementation, delimiting the region of interest (ROI) for face detection, eye detection and iris detection. The system robustness allow the eye tracking system to control the mouse using eye movements allowing disable users to communicate through a communication interface. The hardware required is simple and based in an high definition webcam. The face detection and eye detection processes are based on the Viola Jones technique; iris detection and tracking are based on the Hough Transform. The usage of local processing reduces the computational cost and even working with high definition stream leads to a performance 33% better than the base system. The system presented here was compared with a commercial system and a set of equipment were tested in order to dene the best set up for the eye tracking system and to validate the work presented here. Future work is presented at the end in order to allow the project continuity. / O rastreamento ocular para usuários com problemas motores é um estudo importante na área de Interface Humano-Computador (IHC). Com o objetivo de fornecer um sistema de rastreamento ocular de baixo custo, este trabalho apresenta uma nova abordagem para um sistema robusto e com alto desempenho. Com relação ao trabalho base para esta pesquisa, a implementação proposta contém inovações em todas as etapas do processo envolvendo o rastreamento ocular, desde a detecção da região da face e dos olhos até a detecção da íris. Neste trabalho, foi utilizado o conceito de processamento local, delimitando as regiões de interesse em todas as etapas do processo: detecção da região da face, região dos olhos e região da íris. Este trabalho permite que pessoas possam efetuar ações controlando o mouse através do movimento dos olhos em uma interface de rastreamento ocular, utilizando apenas equipamentos de uso comum, como, por exemplo, uma webcam. O processo de detecção da face e detecção ocular foi feito através da técnica de Viola e Jones. Para a detecção e rastreamento da íris foi utilizada a Transformada de Hough, e utilização de regiões de interesse com o objetivo de limitar a área de processamento da imagem, e consequentemente, o custo computacional, resultando em uma aplicação com um melhor desempenho e robustez em todas as etapas. Obteve-se um ganho de até 33% em relação ao tempo de processamento do sistema, quando comparado com o sistema base, porém, operando com imagens em alta definição. Foi realizada ainda uma comparação com sistemas de rastreamento ocular de uso comercial e diferentes tipos de equipamentos para validar as técnicas estudadas neste trabalho.

Context. Automatic placement of surveillance cameras' 3D models in an arbitrary floor plan containing obstacles is a challenging task. The problem becomes more complex when different types of region of interest (RoI) and minimum resolution are considered. An automatic camera placement decision support system (ACP-DSS) integrated into a 3D CAD environment could assist the surveillance system designers with the process of finding good camera settings considering multiple constraints. Objectives. In this study we designed and implemented two subsystems: a camera toolset in SketchUp (CTSS) and a decision support system using an enhanced Particle Swarm Optimization (PSO) algorithm (HPSO-DSS). The objective for the proposed algorithm was to have a good computational performance in order to quickly generate a solution for the automatic camera placement (ACP) problem. The new algorithm benefited from different aspects of other heuristics such as hill-climbing and greedy algorithms as well as a number of new enhancements. Methods. Both CTSS and ACP-DSS were designed and constructed using the information technology (IT) research framework. A state-of-the-art evolutionary optimization method, Hybrid PSO (HPSO), implemented to solve the ACP problem, was the core of our decision support system. Results. The CTSS is evaluated by some of its potential users after employing it and later answering a conducted survey. The evaluation of CTSS confirmed an outstanding satisfactory level of the respondents. Various aspects of the HPSO algorithm were compared to two other algorithms (PSO and Genetic Algorithm), all implemented to solve our ACP problem. Conclusions. The HPSO algorithm provided an efficient mechanism to solve the ACP problem in a timely manner. The integration of ACP-DSS into CTSS might aid the surveillance designers to adequately and more easily plan and validate the design of their security systems. The quality of CTSS as well as the solutions offered by ACP-DSS were confirmed by a number of field experts. / Sarmad Rohani: 004670606805 Reza Shams: 0046704030897

The conceptual rainfall-runoff model Hysim is used to estimate the flow in ungauged catchments in Scotland by Scottish Water. However, there are non-quantified uncertainties associated with the outcomes of the modelling strategy used. In order to identify and quantify these uncertainties it was necessary to use the framework of proxy-basin validation in order to evaluate the performance of different modelling strategies.   The proxy-basin validation test requires hydrologically analogous catchments for the evaluation of models, a Region Of Influence regionalisation method was used in order group selected catchments by Q95(%MF). Four groups of four catchments were established, which covered Q95(%MF) 5-7%, 7-9%, 9-11% and 11-13%.   The allocation of “donor catchment” and “target catchment” for each Q95(%MF) group was accomplished through discussion with Scottish Water with respect to existing Scottish Water modelled catchments. A single donor catchment and three target catchments were therefore indicated for each group.   Two modelling strategies were developed by the study; the first full transposition method used the entire optimised parameter-set from the donor catchment with the exception of the target catchment’s “catchment area” parameter. The second partial transposition method used the entire optimal parameter-set with the exception of the target catchment’s “interception storage”, “time to peak”, “rooting depth” and “catchment area” parameters.    It was found that the full transposition method had the least uncertainty associated its use for flow estimation when the parameter-set was derived from a donor catchment calibration that was excellent. Contrarily, it was found that the partial transposition model method had the least uncertainty associated with flow estimation for parameter-sets that were derived from a relatively poor donor catchment calibration.   Encouraged by this testing framework, this study has suggested the use of catalogue of donor parameter-sets that can be used to estimate flow for catchments that are hydrologically similar. This strategy of hydrological modelling has been recommended to improve existing Scottish Water Hysim methodology.

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