Particle displacement tracking for PIV

A new Particle Imaging Velocimetry (PIV) data acquisition and analysis system, which is an order of magnitude faster than any previously proposed system has been constructed and tested. The new Particle Displacement Tracing (PDT) system is an all electronic technique employing a video camera and a large memory buffer frame-grabber board. Using a simple encoding scheme, a time sequence of single exposure images are time coded into a single image and then processed to track particle displacements and determine velocity vectors. Application of the PDT technique to a counter-rotating vortex flow produced over 1100 velocity vectors in 110 seconds when processed on an 80386 PC

Advanced methods and deep learning for video and satellite data compression

L'abstract è presente nell'allegato / the abstract is in the attachmen

Towards Joint Super-Resolution and High Dynamic Range Image Reconstruction

The main objective for digital image- and video camera systems is to reproduce a real-world scene in such a way that a high visual quality is obtained. A crucial aspect in this regard is, naturally, the quality of the hardware components of the camera device. There are, however, always some undesired limitations imposed by the sensor of the camera. To begin with, the dynamic range of light intensities that the sensor can capture in its nonsaturated region is much smaller than the dynamic range of most common daylight scenes. Secondly, the achievable spatial resolution of the camera is limited, especially for video capture with a high frame rate. Signal processing software algorithms can be used that fuse the information from a sequence of images into one enhanced image. Thus, the dynamic range limitation can be overcome, and the spatial resolution can be improved. This thesis discusses different methods that utilize data from a set of multiple images, that exhibits photometric diversity, spatial diversity, or both. For the case where the images are differently exposed, photometric alignment is performed prior to reconstructing an image of a higher dynamic range. For the case where there is spatial diversity, a Super-Resolution reconstruction method is applied, in which an inverse problem is formulated and solved to obtain a high resolution reconstruction result. For either case, as well as for the optimistic and promising combination of the two methods, the problem formulation should consider how the scene information is perceived by humans. Incorporating the properties of the human vision system in novel mathematical formulations for joint high dynamic range and high resolution image reconstruction is the main contribution of the thesis, in particular of the published papers that are included. The potential usefulness of high dynamic range image reconstruction on the one hand, and Super-Resolution image reconstruction on the other, are demonstrated. Finally, the combination of the two is discussed and results from simulations are given

Selected Topics in Bayesian Image/Video Processing

In this dissertation, three problems in image deblurring, inpainting and virtual content insertion are solved in a Bayesian framework.;Camera shake, motion or defocus during exposure leads to image blur. Single image deblurring has achieved remarkable results by solving a MAP problem, but there is no perfect solution due to inaccurate image prior and estimator. In the first part, a new non-blind deconvolution algorithm is proposed. The image prior is represented by a Gaussian Scale Mixture(GSM) model, which is estimated from non-blurry images as training data. Our experimental results on a total twelve natural images have shown that more details are restored than previous deblurring algorithms.;In augmented reality, it is a challenging problem to insert virtual content in video streams by blending it with spatial and temporal information. A generic virtual content insertion (VCI) system is introduced in the second part. To the best of my knowledge, it is the first successful system to insert content on the building facades from street view video streams. Without knowing camera positions, the geometry model of a building facade is established by using a detection and tracking combined strategy. Moreover, motion stabilization, dynamic registration and color harmonization contribute to the excellent augmented performance in this automatic VCI system.;Coding efficiency is an important objective in video coding. In recent years, video coding standards have been developing by adding new tools. However, it costs numerous modifications in the complex coding systems. Therefore, it is desirable to consider alternative standard-compliant approaches without modifying the codec structures. In the third part, an exemplar-based data pruning video compression scheme for intra frame is introduced. Data pruning is used as a pre-processing tool to remove part of video data before they are encoded. At the decoder, missing data is reconstructed by a sparse linear combination of similar patches. The novelty is to create a patch library to exploit similarity of patches. The scheme achieves an average 4% bit rate reduction on some high definition videos

MedLAN: Compact mobile computing system for wireless information access in emergency hospital wards

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.As the need for faster, safer and more efficient healthcare delivery increases, medical consultants seek new ways of implementing a high quality telemedical system, using innovative technology. Until today, teleconsultation (the most common application of Telemedicine) was performed by transferring the patient from the Accidents and Emergency ward, to a specially equipped room, or by moving large and heavy machinery to the place where the patient resided. Both these solutions were unpractical, uneconomical and potentially dangerous. At the same time wireless networks became increasingly useful in point-of-care areas such as hospitals, because of their ease of use, low cost of installation and increased flexibility. This thesis presents an integrated system called MedLAN dedicated for use inside the A&E hospital wards. Its purpose is to wirelessly support high-quality live video, audio, high-resolution still images and networks support from anywhere there is WLAN coverage. It is capable of transmitting all of the above to a consultant residing either inside or outside the hospital, or even to an external place, thorough the use of the Internet. To implement that, it makes use of the existing IEEE 802.11b wireless technology. Initially, this thesis demonstrates that for specific scenarios (such as when using WLANs), DICOM specifications should be adjusted to accommodate for the reduced WLAN bandwidth. Near lossless compression has been used to send still images through the WLANs and the results have been evaluated by a number of consultants to decide whether they retain their diagnostic value. The thesis further suggests improvements on the existing 802.11b protocol. In particular, as the typical hospital environment suffers from heavy RF reflections, it suggests that an alternative method of modulation (OFDM) can be embedded in the 802.11b hardware to reduce the multipath effect, increase the throughput and thus the video quality sent by the MedLAN system. Finally, realising that the trust between a patient and a doctor is fundamental this thesis proposes a series of simple actions aiming at securing the MedLAN system. Additionally, a concrete security system is suggested, that encapsulates the existing WEP security protocol, over IPSec

Combined Industry, Space and Earth Science Data Compression Workshop

The sixth annual Space and Earth Science Data Compression Workshop and the third annual Data Compression Industry Workshop were held as a single combined workshop. The workshop was held April 4, 1996 in Snowbird, Utah in conjunction with the 1996 IEEE Data Compression Conference, which was held at the same location March 31 - April 3, 1996. The Space and Earth Science Data Compression sessions seek to explore opportunities for data compression to enhance the collection, analysis, and retrieval of space and earth science data. Of particular interest is data compression research that is integrated into, or has the potential to be integrated into, a particular space or earth science data information system. Preference is given to data compression research that takes into account the scien- tist's data requirements, and the constraints imposed by the data collection, transmission, distribution and archival systems

Object-based 3-d motion and structure analysis for video coding applications

Ankara : Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 1997.Thesis (Ph.D.) -- -Bilkent University, 1997.Includes bibliographical references leaves 102-115Novel 3-D motion analysis tools, which can be used in object-based video codecs, are proposed. In these tools, the movements of the objects, which are observed through 2-D video frames, are modeled in 3-D space. Segmentation of 2-D frames into objects and 2-D dense motion vectors for each object are necessary as inputs for the proposed 3-D analysis. 2-D motion-based object segmentation is obtained by Gibbs formulation; the initialization is achieved by using a fast graph-theory based region segmentation algorithm which is further improved to utilize the motion information. Moreover, the same Gibbs formulation gives the needed dense 2-D motion vector field. The formulations for the 3-D motion models are given for both rigid and non- rigid moving objects. Deformable motion is modeled by a Markov random field which permits elastic relations between neighbors, whereas, rigid 3-D motion parameters are estimated using the E-matrix method. Some improvements on the E-matrix method are proposed to make this algorithm more robust to gross errors like the consequence of incorrect segmentation of 2-D correspondences between frames. Two algorithms are proposed to obtain dense depth estimates, which are robust to input errors and suitable for encoding, respectively. While the former of these two algorithms gives simply a MAP estimate, the latter uses rate-distortion theory. Finally, 3-D motion models are further utilized for occlusion detection and motion compensated temporal interpolation, and it is observed that for both applications 3-D motion models have superiority over their 2-D counterparts. Simulation results on artificial and real data show the advantages of the 3-D motion models in object-based video coding algorithms.Alatan, A AydinPh.D

Digital Image Processing

This book presents several recent advances that are related or fall under the umbrella of 'digital image processing', with the purpose of providing an insight into the possibilities offered by digital image processing algorithms in various fields. The presented mathematical algorithms are accompanied by graphical representations and illustrative examples for an enhanced readability. The chapters are written in a manner that allows even a reader with basic experience and knowledge in the digital image processing field to properly understand the presented algorithms. Concurrently, the structure of the information in this book is such that fellow scientists will be able to use it to push the development of the presented subjects even further

Image Restoration Methods for Retinal Images: Denoising and Interpolation

Retinal imaging provides an opportunity to detect pathological and natural age-related physiological changes in the interior of the eye. Diagnosis of retinal abnormality requires an image that is sharp, clear and free of noise and artifacts. However, to prevent tissue damage, retinal imaging instruments use low illumination radiation, hence, the signal-to-noise ratio (SNR) is reduced which means the total noise power is increased. Furthermore, noise is inherent in some imaging techniques. For example, in Optical Coherence Tomography (OCT) speckle noise is produced due to the coherence between the unwanted backscattered light. Improving OCT image quality by reducing speckle noise increases the accuracy of analyses and hence the diagnostic sensitivity. However, the challenge is to preserve image features while reducing speckle noise. There is a clear trade-off between image feature preservation and speckle noise reduction in OCT. Averaging multiple OCT images taken from a unique position provides a high SNR image, but it drastically increases the scanning time. In this thesis, we develop a multi-frame image denoising method for Spectral Domain OCT (SD-OCT) images extracted from a very close locations of a SD-OCT volume. The proposed denoising method was tested using two dictionaries: nonlinear (NL) and KSVD-based adaptive dictionary. The NL dictionary was constructed by adding phases, polynomial, exponential and boxcar functions to the conventional Discrete Cosine Transform (DCT) dictionary. The proposed denoising method denoises nearby frames of SD-OCT volume using a sparse representation method and combines them by selecting median intensity pixels from the denoised nearby frames. The result showed that both dictionaries reduced the speckle noise from the OCT images; however, the adaptive dictionary showed slightly better results at the cost of a higher computational complexity. The NL dictionary was also used for fundus and OCT image reconstruction. The performance of the NL dictionary was always better than that of other analytical-based dictionaries, such as DCT and Haar. The adaptive dictionary involves a lengthy dictionary learning process, and therefore cannot be used in real situations. We dealt this problem by utilizing a low-rank approximation. In this approach SD-OCT frames were divided into a group of noisy matrices that consist of non-local similar patches. A noise-free patch matrix was obtained from a noisy patch matrix utilizing a low-rank approximation. The noise-free patches from nearby frames were averaged to enhance the denoising. The denoised image obtained from the proposed approach was better than those obtained by several state-of-the-art methods. The proposed approach was extended to jointly denoise and interpolate SD-OCT image. The results show that joint denoising and interpolation method outperforms several existing state-of-the-art denoising methods plus bicubic interpolation.4 month