Historical photos are significant attestations of the inheritance of the past. Since Photography is an art that is more than 150 years old, more and more diffuse are the photographic archives all over the world. Nevertheless, time and bad preservation corrupts physical supports, and many important historical documents risk to be ruined and their content lost. Therefore solutions must be implemented to preserve their state and to recover damaged information. This PhD thesis proposes a general methodology, and several applicative solutions, to handle these problems, by means of digitization and digital restoration. The purpose is to create a useful tool to support non-expert users in the restoration process of damaged historical images. The content of this thesis is outlined as follows: Chapter 1 gives an overview on the problems related to management and preservation of cultural repositories, and discusses about ...

During the past two decades, image compression has developed from a mostly academic Rate-Distortion (R-D) field, into a highly commercial business. Various lossless and lossy image coding techniques have been developed. This thesis represents an interdisciplinary work between the field of astronomy and digital image processing and brings new aspects into both of the fields. In fact, image compression had its beginning in an American space program for efficient data storage. The goal of this research work is to recognize and develop new methods for space observatories and software tools to incorporate compression in space astronomy standards. While the astronomers benefit from new objective processing and analysis methods and improved efficiency and quality, for technicians a new field of application and research is opened. For validation of the processing results, the case of InfraRed (IR) astronomy has been specifically analyzed. ...

The recent invasion of stereoscopic 3D television technologies is expected to be followed by autostereoscopic and holographic technologies. Glasses-free multiple stereoscopic pair displaying capabilities of these technologies will advance the 3D experience. The prospective 3D format to create the multiple views for such displays is Multiview Video plus Depth (MVD) format based on the Depth Image Based Rendering (DIBR) techniques. The depth modality of the MVD format is an active research area whose main objective is to develop DIBR friendly efficient compression methods. As a part this research, the thesis proposes novel 3D planar-based depth representations. The planar approximation of the stereo depth images is formulated as an energy-based co-segmentation problem by a Markov Random Field model. The energy terms of this problem are designed to mimic the rate-distortion tradeoff for a depth compression application. A heuristic algorithm is developed ...

Recent advances in many fields ranging from engineering to natural science, require increasingly complicated optimization tasks in the experiment design, for which the target objectives are generally in the form of black-box functions that are expensive to evaluate. In a common formulation of this problem, a designer is expected to solve the black-box optimization tasks via sequentially attempting candidate solutions and receiving feedback from the system. This thesis considers Bayesian optimization (BO) as the black-box optimization framework, and investigates the enhancements on BO from the aspects of efficiency, adaptation and reliability. Generally, BO consists of a surrogate model for providing probabilistic inference and an acquisition function which leverages the probabilistic inference for selecting the next candidate solution. Gaussian process (GP) is a prominent non-parametric surrogate model, and the quality of its inference is a critical factor on the optimality performance ...

In order to meet the market demand for high datarates, most digital wireless communication systems rely on broadband channels and therefore suffer from Inter Symbol Interference (ISI), a phenomenon that needs to be combatted at the receiver by appropriate equalization techniques in order to restore the transmitted information. In this context, block transmission techniques based on the use of a Cyclic-Prefix (CP) have attracted a lot of attention in the last years for they allow an efficient and computationally cheap ISI cancellation procedure. Historically, OFDM (Orthogonal Frequency Division Multiplexing) was the first proposed block transmission scheme and has been adopted in numerous standards for high-speed data transmission in both wired and wireless applications. In the wireless context however, OFDM suffers of several problems, both on an implementational point of view and from a performance perspective. Some recently proposed block transmission ...

In lossless coding, compresssion and decompression of source data result in the exact recovery of the individual elements of the original source data. Lossless image / video coding is necessary in applications where no loss of pixel values is tolerable. Examples are medical imaging, remote sensing, in image/video archives and studio applications where tandem- and trans-coding are used in editing, which can lead to accumulating errors. Nearly-lossless coding is used in applications where a small error, defined as a maximum error or as a root mean square (rms) error, is tolerable. In lossless embedded coding, a losslessly coded bit stream can be decoded at any bit rate lower than the lossless bit rate. In this thesis, research on embedded lossless video coding based on a motion compensated framework, similar to that of MPEG-2, is presented. Transforms that map integers into ...

Digital signal processing (DSP), and, in particular, image processing, has been studied for many years. However, only the recent advances in computing technology have made it possible to use DSP in day-to-day applications. Images are now commonly used in many applications. The increasingly ubiquitous use of images raises new challenges. Users expect the images to be transmitted in a minimum of time and to take up as little storage space as possible. These requirements call for efficient image compression algorithms. The users want this compression and decompression process to be very fast so as not to have to wait for an image to be usable. Therefore, the complexities of compression algorithms need to be studied. In this thesis the term complexity is be linked to the execution time of an algorithm. That is, the lower the complexity of an algorithm, ...

Digital holography is a discipline of science that measures or reconstructs the wavefield of light by means of interference. The wavefield encodes three-dimensional information, which has many applications, such as interferometry, microscopy, non-destructive testing and data storage. Moreover, digital holography is emerging as a display technology. Holograms can recreate the wavefield of a 3D object, thereby reproducing all depth cues for all viewpoints, unlike current stereoscopic 3D displays. At high quality, the appearance of an object on a holographic display system becomes indistinguishable from a real one. High-quality holograms need large volumes of data to be represented, approaching resolutions of billions of pixels. For holographic videos, the data rates needed for transmitting and encoding of the raw holograms quickly become unfeasible with currently available hardware. Efficient generation and coding of holograms will be of utmost importance for future holographic displays. ...

This dissertation investigates robust signal processing and machine learning techniques, with the objective of improving the robustness of two applications against various threats, namely Global Navigation Satellite System (GNSS) based positioning and satellite imaging. GNSS technology is widely used in different fields, such as autonomous navigation, asset tracking, or smartphone positioning, while the satellite imaging plays a central role in monitoring, detecting and estimating the intensity of key natural phenomena, such as flooding prediction and earthquake detection. Considering the use of both GNSS positioning and satellite imaging in critical and safety-of-life applications, it is necessary to protect those two technologies from either intentional or unintentional threats. In the real world, the common threats to GNSS technology include multipath propagation and intentional/unintentional interferences. This thesis investigates methods to mitigate the influence of such sources of error, with the final objective of ...

In this thesis, we examine the problem of algorithmic analysis of complex audio scenes with a special emphasis on natural audio scenes. One of the driving goals behind this work is to develop tools for monitoring the presence of animals in areas of interest based on their vocalisations. This task, which often occurs in the evaluation of nature conservation measures, leads to a number of subproblems in audio scene analysis. In order to develop and evaluate pattern recognition algorithms for animal sounds, a representative collection of such sounds is necessary. Building such a collection is beyond the scope of a single researcher and we therefore use data from the Animal Sound Archive of the Humboldt University of Berlin. Although a large portion of well annotated recordings from this archive has been available in digital form, little infrastructure for searching and ...

Next generation search engines will enable query formulations, other than text, relying on visual information encoded in terms of images and shapes. The 3D search technology, in particular, targets specialized application domains ranging from computer aided-design and manufacturing to cultural heritage archival and presentation. Content-based retrieval research aims at developing search engines that would allow users to perform a query by similarity of content. This thesis deals with two fundamentals problems in content-based 3D object retrieval: (1) How to describe a 3D shape to obtain a reliable representative for the subsequent task of similarity search? (2) How to supervise the search process to learn inter-shape similarities for more effective and semantic retrieval? Concerning the first problem, we develop a novel 3D shape description scheme based on probability density of multivariate local surface features. We constructively obtain local characterizations of 3D ...

The recent progress in artificial neural networks (rebranded as “deep learning”) has significantly boosted the state-of-the-art in numerous domains of computer vision offering an opportunity to approach the problems which were hardly solvable with conventional machine learning. Thus, in the frame of this PhD study, we explore how deep learning techniques can help in the analysis of one the most basic and essential semantic traits revealed by a human face, namely, gender and age. In particular, two complementary problem settings are considered: (1) gender/age prediction from given face images, and (2) synthesis and editing of human faces with the required gender/age attributes. Convolutional Neural Network (CNN) has currently become a standard model for image-based object recognition in general, and therefore, is a natural choice for addressing the first of these two problems. However, our preliminary studies have shown that the ...

In biological research images are extensively used to monitor growth, dynamics and changes in biological specimen, such as cells or plants. Many of these images are used solely for observation or are manually annotated by an expert. In this dissertation we discuss several methods to automate the annotating and analysis of bio-images. Two large clusters of methods have been investigated and developed. A first set of methods focuses on the automatic delineation of relevant objects in bio-images, such as individual cells in microscopic images. Since these methods should be useful for many different applications, e.g. to detect and delineate different objects (cells, plants, leafs, ...) in different types of images (different types of microscopes, regular colour photographs, ...), the methods should be easy to adjust. Therefore we developed a methodology relying on probability theory, where all required parameters can easily ...

Visual information, in the form of digital images and videos, has become so omnipresent in computer databases and repositories, that it can no longer be considered a “second class citizen”, eclipsed by textual information. In that scenario, image classification has become a critical task. In particular, the pursuit of automatic identification of complex semantical concepts represented in images, such as scenes or objects, has motivated researchers in areas as diverse as Information Retrieval, Computer Vision, Image Processing and Artificial Intelligence. Nevertheless, in contrast to text documents, whose words carry semantic, images consist of pixels that have no semanticinformation by themselves, making the task very challenging. In this dissertation, we have addressed the problem of representing images based on their visual information. Our aim is content-based concept detection in images and videos, with a novel representation that enriches the Bag-of-Words model. ...

Optimizing the performance of digital imaging systems with respect to the capture, display, storage and transmission of visual information represents one of the biggest challenges in the field of image and video processing. Taking into account the way humans perceive visual information can be greatly beneficial for this task. To achieve this, it is necessary to understand and model the human visual system, which is also the principal goal of this thesis. Computational models for different aspects of the visual system are developed, which can be used in a wide variety of image and video processing applications. The proposed models and metrics are shown to be consistent with human perception. The focus of this work is visual quality assessment. A perceptual distortion metric (PDM) for the evaluation of video quality is presented. It is based on a model of the ...