The evolution of depth‐perception visualization technologies, emerging format standardization work and research within the field of multi‐view 3D video and imagery addresses the need for flexible 3D video visualization. The wide variety of available 3D‐display types and visualization techniques for multi‐view video, as well as the high throughput requirements for high definition video, addresses the need for a real‐time 3D video playback solution that takes advantage of hardware accelerated graphics, while providing a high degree of flexibility through format configuration and cross‐platform interoperability. A modular component based software solution based on FFmpeg for video demultiplexing and video decoding is proposed,using OpenGL and GLUT for hardware accelerated graphics and POSIX threads for increased CPU utilization. The solution has been verified to have sufficient throughput in order to display 1080p video at the native video frame rate on the experimental system, which is considered as a standard high‐end desktop PC only using commercial hardware. In order to evaluate the performance of the proposed solution a number of throughput evaluation metrics have been introduced measuring average frame rate as a function of: video bit rate, video resolution and number of views. The results obtained have indicated that the GPU constitutes the primary bottleneck in a multi‐view lenticular rendering system and that multi‐view rendering performance is degraded as the number of views is increased. This is a result of the current GPU square matrix texture cache architectures, resulting in texture lookup access times according to random memory access patterns when the number of views is high. The proposed solution has been identified in order to provide low CPU efficiency, i.e. low CPU hardware utilization and it is recommended to increase performance by investigating the gains of scalable multithreading techniques. It is also recommended to investigate the gains of introducing video frame buffering in video memory or to move more calculations to the CPU in order to increase GPU performance.

This master's thesis deals with lossless video compression. This thesis includes basic concepts and techniques used in image representation. The reader can find an explanation of basic difference between lossless video compression and lossy video compression and lossless video compression limitations. There is also possible find a description of the basic blocks forming the video codec (every block is described in detail). In every block there are introduced its possible variants. Implemented lossless videocodec was compared with common lossless videocodecs.

The aim of this project is to design and create application for the visualization of interconnected video data. Visualization takes place in 3D space and seeks to exploit its advantages (such as depth perception). This document contains survey to different categories of spatial user interfaces. In addition, includes three possible designs of user interfaces and control. Implementation details and made usability tests are also described. Application is implemented in C++ using Open Inventor. The document includes evaluation of the results and made tests.

This thesis deals with modern methods of a lossy still image and video compression. Wavelet transformation and SPIHT algorithm also belong to these methods. In second half of this thesis, a videocodec is implemented based on acquired knowledge. This codec uses Daubechies wavelets to analyse an image. Afterwards there is a modified SPIHT algorithm applied on gained coefficients. A lot of effort was put in order to optimize this computation. It is possible to use the created codec in Video for Windows, DirectShow and FFmpeg multimedia frameworks. At the end of this thesis, commonly used codecs are compared with newly created one.

Panoramas or stitched images are used in topographical mapping, panoramic 3D reconstruction, deep space exploration image processing, medical image processing, multimedia broadcasting, system automation, photography and other numerous fields. Generating real-time panoramic images in small embedded computer is of particular importance being lighter, smaller and mobile imaging system. Moreover, this type of lightweight panoramic imaging system is used for different types of industrial or home inspection. A real-time handheld panorama imaging system is developed using embedded real-time Linux as software module and Gumstix Overo and PandaBoard ES as hardware module. The proposed algorithm takes 62.6602 milliseconds to generate a panorama frame from three images using a homography matrix. Hence, the proposed algorithm is capable of generating panorama video with 15.95909365 frames per second. However, the algorithm is capable to be much speedier with more optimal homography matrix. During the development, Ångström Linux and Ubuntu Linux are used as the operating system with Gumstix Overo and PandaBoard ES respectively. The real-time kernel patch is used to configure the non-real-time Linux distribution for real-time operation. The serial communication software tools C-Kermit, Minicom are used for terminal emulation between development computer and small embedded computer. The software framework of the system consist UVC driver, V4L/V4L2 API, OpenCV API, FFMPEG API, GStreamer, x264, Cmake, Make software packages. The software framework of the system also consist stitching algorithm that has been adopted from available stitching methods with necessary modification. Our proposed stitching process automatically finds out motion model of the Spherical camera system and saves the matrix in a look file. The extracted homography matrix is then read from look file and used to generate real-time panorama image. The developed system generates real-time 180° view panorama image from a spherical camera system. Beside, a test environment is also developed to experiment calibration and real-time stitching with different image parameters. It is able to take images with different resolutions as input and produce high quality real-time panorama image. The QT framework is used to develop a multifunctional standalone software that has functions for displaying real-time process algorithm performance in real-time through data visualization, camera system calibration and other stitching options. The software runs both in Linux and Windows. Moreover, the system has been also realized as a prototype to develop a chimney inspection system for a local company. / Main Uddin-Al-Hasan, E-mail: main.hasan@gmail.com