119 research outputs found
Construction de mosaïques de super-résolution à partir de la vidéo de basse résolution. Application au résumé vidéo et la dissimulation d'erreurs de transmission.
La numĂ©risation des vidĂ©os existantes ainsi que le dĂ©veloppement explosif des services multimĂ©dia par des rĂ©seaux comme la diffusion de la tĂ©lĂ©vision numĂ©rique ou les communications mobiles ont produit une Ă©norme quantitĂ© de vidĂ©os compressĂ©es. Ceci nĂ©cessite des outils dâindexation et de navigation efficaces, mais une indexation avant lâencodage nâest pas habituelle. Lâapproche courante est le dĂ©codage complet des ces vidĂ©os pour ensuite crĂ©er des indexes. Ceci est trĂšs coĂ»teux et par consĂ©quent non rĂ©alisable en temps rĂ©el. De plus, des informations importantes comme le mouvement, perdus lors du dĂ©codage, sont reestimĂ©es bien que dĂ©jĂ prĂ©sentes dans le flux comprimĂ©. Notre but dans cette thĂšse est donc la rĂ©utilisation des donnĂ©es dĂ©jĂ prĂ©sents dans le flux comprimĂ© MPEG pour lâindexation et la navigation rapide. Plus prĂ©cisĂ©ment, nous extrayons des coefficients DC et des vecteurs de mouvement. Dans le cadre de cette thĂšse, nous nous sommes en particulier intĂ©ressĂ©s Ă la construction de mosaĂŻques Ă partir des images DC extraites des images I. Une mosaĂŻque est construite par recalage et fusion de toutes les images dâune sĂ©quence vidĂ©o dans un seul systĂšme de coordonnĂ©es. Ce dernier est en gĂ©nĂ©ral alignĂ© avec une des images de la sĂ©quence : lâimage de rĂ©fĂ©rence. Il en rĂ©sulte une seule image qui donne une vue globale de la sĂ©quence. Ainsi, nous proposons dans cette thĂšse un systĂšme complet pour la construction des mosaĂŻques Ă partir du flux MPEG-1/2 qui tient compte de diffĂ©rentes problĂšmes apparaissant dans des sĂ©quences vidĂ©o rĂ©eles, comme par exemple des objets en mouvment ou des changements dâĂ©clairage. Une tĂąche essentielle pour la construction dâune mosaĂŻque est lâestimation de mouvement entre chaque image de la sĂ©quence et lâimage de rĂ©fĂ©rence. Notre mĂ©thode se base sur une estimation robuste du mouvement global de la camĂ©ra Ă partir des vecteurs de mouvement des images P. Cependant, le mouvement global de la camĂ©ra estimĂ© pour une image P peut ĂȘtre incorrect car il dĂ©pend fortement de la prĂ©cision des vecteurs encodĂ©s. Nous dĂ©tectons les images P concernĂ©es en tenant compte des coefficients DC de lâerreur encodĂ©e associĂ©e et proposons deux mĂ©thodes pour corriger ces mouvements. UnemosaĂŻque construite Ă partir des images DC a une rĂ©solution trĂšs faible et souffre des effets dâaliasing dus Ă la nature des images DC. Afin dâaugmenter sa rĂ©solution et dâamĂ©liorer sa qualitĂ© visuelle, nous appliquons une mĂ©thode de super-rĂ©solution basĂ©e sur des rĂ©tro-projections itĂ©ratives. Les mĂ©thodes de super-rĂ©solution sont Ă©galement basĂ©es sur le recalage et la fusion des images dâune sĂ©quence vidĂ©o, mais sont accompagnĂ©es dâune restauration dâimage. Dans ce cadre, nous avons dĂ©veloppĂ© une nouvellemĂ©thode dâestimation de flou dĂ» au mouvement de la camĂ©ra ainsi quâune mĂ©thode correspondante de restauration spectrale. La restauration spectrale permet de traiter le flou globalement, mais, dans le cas des obvi jets ayant un mouvement indĂ©pendant du mouvement de la camĂ©ra, des flous locaux apparaissent. Câest pourquoi, nous proposons un nouvel algorithme de super-rĂ©solution dĂ©rivĂ© de la restauration spatiale itĂ©rative de Van Cittert et Jansson permettant de restaurer des flous locaux. En nous basant sur une segmentation dâobjets en mouvement, nous restaurons sĂ©parĂ©ment lamosaĂŻque dâarriĂšre-plan et les objets de lâavant-plan. Nous avons adaptĂ© notre mĂ©thode dâestimation de flou en consĂ©quence. Dans une premier temps, nous avons appliquĂ© notre mĂ©thode Ă la construction de rĂ©sumĂ© vidĂ©o avec pour lâobjectif la navigation rapide par mosaĂŻques dans la vidĂ©o compressĂ©e. Puis, nous Ă©tablissions comment la rĂ©utilisation des rĂ©sultats intermĂ©diaires sert Ă dâautres tĂąches dâindexation, notamment Ă la dĂ©tection de changement de plan pour les images I et Ă la caractĂ©risation dumouvement de la camĂ©ra. Enfin, nous avons explorĂ© le domaine de la rĂ©cupĂ©ration des erreurs de transmission. Notre approche consiste en construire une mosaĂŻque lors du dĂ©codage dâun plan ; en cas de perte de donnĂ©es, lâinformation manquante peut ĂȘtre dissimulĂ©e grace Ă cette mosaĂŻque
Error Resilient Video Coding Using Bitstream Syntax And Iterative Microscopy Image Segmentation
There has been a dramatic increase in the amount of video traffic over the Internet in past several years. For applications like real-time video streaming and video conferencing, retransmission of lost packets is often not permitted. Popular video coding standards such as H.26x and VPx make use of spatial-temporal correlations for compression, typically making compressed bitstreams vulnerable to errors. We propose several adaptive spatial-temporal error concealment approaches for subsampling-based multiple description video coding. These adaptive methods are based on motion and mode information extracted from the H.26x video bitstreams. We also present an error resilience method using data duplication in VPx video bitstreams.
A recent challenge in image processing is the analysis of biomedical images acquired using optical microscopy. Due to the size and complexity of the images, automated segmentation methods are required to obtain quantitative, objective and reproducible measurements of biological entities. In this thesis, we present two techniques for microscopy image analysis. Our first method, âJelly Fillingâ is intended to provide 3D segmentation of biological images that contain incompleteness in dye labeling. Intuitively, this method is based on filling disjoint regions of an image with jelly-like fluids to iteratively refine segments that represent separable biological entities. Our second method selectively uses a shape-based function optimization approach and a 2D marked point process simulation, to quantify nuclei by their locations and sizes. Experimental results exhibit that our proposed methods are effective in addressing the aforementioned challenges
Error-resilient multi-view video plus depth based 3-D video coding
Three Dimensional (3-D) video, by definition, is a collection of signals that can provide depth perception of a 3-D scene. With the development of 3-D display
technologies and interactive multimedia systems, 3-D video has attracted significant interest from both industries and academia with a variety of applications. In order to provide desired services in various 3-D video applications, the multiview video plus depth (MVD) representation, which can facilitate the generation of virtual views, has been determined to be the best format for 3-D video data.
Similar to 2-D video, compressed 3-D video is highly sensitive to transmission errors due to errors propagated from the current frame to the future predicted frames. Moreover, since the virtual views required for auto-stereoscopic displays are rendered from the compressed texture videos and depth maps, transmission
errors of the distorted texture videos and depth maps can be further propagated to the virtual views. Besides, the distortions in texture and depth show different
effects on the rendering views. Therefore, compared to the reliability of the transmission of the 2-D video, error-resilient texture video and depth map coding
are facing major new challenges.
This research concentrates on improving the error resilience performance of MVD-based 3-D video in packet loss scenarios. Based on the analysis of the propagating behaviour of transmission errors, a Wyner-Ziv (WZ)-based error-resilient algorithm is first designed for coding of the multi-view video data or depth data. In this scheme, an auxiliary redundant stream encoded according to WZ principle
is employed to protect a primary stream encoded with standard multi-view video coding codec. Then, considering the fact that different combinations of texture and depth coding mode will exhibit varying robustness to transmission errors, a rate-distortion optimized mode switching scheme is proposed to strike the optimal trade-off between robustness and compression effciency. In this approach,
the texture and depth modes are jointly optimized by minimizing the overall distortion of both the coded and synthesized views subject to a given bit rate. Finally, this study extends the research on the reliable transmission of view synthesis prediction (VSP)-based 3-D video. In order to mitigate the prediction position error caused by packet losses in the depth map, a novel disparity vector correction algorithm is developed, where the corrected disparity vector is calculated from the depth error. To facilitate decoder error concealment, the depth
error is recursively estimated at the decoder.
The contributions of this dissertation are multifold. First, the proposed WZbased error-resilient algorithm can accurately characterize the effect of transmission
error on multi-view distortion at the transform domain in consideration of both temporal and inter-view error propagation, and based on the estimated distortion,
this algorithm can perform optimal WZ bit allocation at the encoder through explicitly developing a sophisticated rate allocation strategy. This proposed algorithm is able to provide a finer granularity in performing rate adaptivity
and unequal error protection for multi-view data, not only at the frame level, but also at the bit-plane level. Secondly, in the proposed mode switching scheme, a
new analytic model is formulated to optimally estimate the view synthesis distortion due to packet losses, in which the compound impact of the transmission distortions of both the texture video and the depth map on the quality of the
synthesized view is mathematically analysed. The accuracy of this view synthesis distortion model is demonstrated via simulation results and, further, the estimated distortion is integrated into a rate-distortion framework for optimal
mode switching to achieve substantial performance gains over state-of-the-art algorithms. Last, but not least, this dissertation provides a preliminary investigation
of VSP-based 3-D video over unreliable channel. In the proposed disparity vector correction algorithm, the pixel-level depth map error can be precisely estimated at the decoder without the deterministic knowledge of the error-free reconstructed depth. The approximation of the innovation term involved in depth error estimation is proved theoretically. This algorithm is very useful to conceal
the position-erroneous pixels whose disparity vectors are correctly received
Recommended from our members
Error control strategies in H.265|HEVC video transmission
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonWith the rapid development in video coding technologies in the last decade, high-resolution video delivery suffers from packet loss due to unreliable transmission channels (time-varying characteristics). The error Resilience approaches at channel coding level are less efficient to implement in real time video transmission as the encoded video samples are in variable code length. Therefore, error resilience in video coding standard plays a vital role to reduce the effect of error propagation and improve the perceived visual quality. The main work in this thesis is to develop an efficient error resilience mechanism for H.265|HEVC video coding standard to reduce the effects of error propagation in error-prone conditions. In this thesis, two error resilience algorithms are proposed. The first one is Adaptive Slice Encoding (ASE) error resilience algorithm. The concept of this algorithm is to extract and protect the most active slices in the coded bitstream based on the adaptive search window. This algorithm can be applied in low delay video transmission with and without using a feedback channel. It is also designed to be compatible with reference coding software manual (HM16) for H.265|HEVC coding standard. The second proposed algorithm is a joint encoder-decoder error resilience called Error resilience based on Supplemental Enhancement Information (ERSEI) algorithm. A feedback message status is used from the decoder to notify the encoder to start encoding clean random-access picture adaptively based on the decoded picture hash message status from the decoder. At the same time, the decoder will be notified to start the error concealment process whilst waiting to receive correct video data. A recovery point message from the decoder feedback channel is used to update the encoder with error messages.
In this thesis, extensive experimental work, evaluation, and comparison with state-of-the-art related algorithms have been conducted to evaluate the proposed algorithms. Furthermore, the best trade-off between the coding efficiency of the proposed error resilience algorithms and error resilience performance has been considered at the design stage. The experimental work evaluation includes both encoding conditions, i.e. error-free and error-prone. The results achieved from the experiments show significant improvements, in (Y-PSNR) results and subjective quality of the decoded bitstream, using the proposed algorithm in error-prone conditions with a variety of packet loss rates.
Moreover, experimental work is conducted to test the algorithms complexity in terms of required processing execution time at both encoding and decoding stages. Additionally, the video coding standard performance for both H.264|AVC and H.265|HEVC coding standards are evaluated in error-free and error-prone environments.
For ASE algorithm and when compared with improved region of interest (IROI) and region of interest (ROI) algorithms, a significant improvement in visual quality was the most obvious finding from the obtained results with PLRs of 2-18 (%).
For ERSEI algorithm and when compared with the default HM16 with pixel copy concealment and motion compensated error concealment (MCEC) techniques, the evaluation results indicate clear visual quality enhancement under different packet loss rates PLRs (1,2 6, 8) %.The Ministry of Higher Education and Scientific Research in Ira
Image analysis using visual saliency with applications in hazmat sign detection and recognition
Visual saliency is the perceptual process that makes attractive objects stand out from their surroundings in the low-level human visual system. Visual saliency has been modeled as a preprocessing step of the human visual system for selecting the important visual information from a scene. We investigate bottom-up visual saliency using spectral analysis approaches. We present separate and composite model families that generalize existing frequency domain visual saliency models. We propose several frequency domain visual saliency models to generate saliency maps using new spectrum processing methods and an entropy-based saliency map selection approach. A group of saliency map candidates are then obtained by inverse transform. A final saliency map is selected among the candidates by minimizing the entropy of the saliency map candidates. The proposed models based on the separate and composite model families are also extended to various color spaces. We develop an evaluation tool for benchmarking visual saliency models. Experimental results show that the proposed models are more accurate and efficient than most state-of-the-art visual saliency models in predicting eye fixation.^ We use the above visual saliency models to detect the location of hazardous material (hazmat) signs in complex scenes. We develop a hazmat sign location detection and content recognition system using visual saliency. Saliency maps are employed to extract salient regions that are likely to contain hazmat sign candidates and then use a Fourier descriptor based contour matching method to locate the border of hazmat signs in these regions. This visual saliency based approach is able to increase the accuracy of sign location detection, reduce the number of false positive objects, and speed up the overall image analysis process. We also propose a color recognition method to interpret the color inside the detected hazmat sign. Experimental results show that our proposed hazmat sign location detection method is capable of detecting and recognizing projective distorted, blurred, and shaded hazmat signs at various distances.^ In other work we investigate error concealment for scalable video coding (SVC). When video compressed with SVC is transmitted over loss-prone networks, the decompressed video can suffer severe visual degradation across multiple frames. In order to enhance the visual quality, we propose an inter-layer error concealment method using motion vector averaging and slice interleaving to deal with burst packet losses and error propagation. Experimental results show that the proposed error concealment methods outperform two existing methods
Error resilient packet switched H.264 video telephony over third generation networks.
Real-time video communication over wireless networks is a challenging problem because
wireless channels suffer from fading, additive noise and interference, which translate
into packet loss and delay. Since modern video encoders deliver video packets with
decoding dependencies, packet loss and delay can significantly degrade the video quality
at the receiver. Many error resilience mechanisms have been proposed to combat packet
loss in wireless networks, but only a few were specifically designed for packet switched
video telephony over Third Generation (3G) networks.
The first part of the thesis presents an error resilience technique for packet switched
video telephony that combines application layer Forward Error Correction (FEC) with
rateless codes, Reference Picture Selection (RPS) and cross layer optimization. Rateless
codes have lower encoding and decoding computational complexity compared to traditional
error correcting codes. One can use them on complexity constrained hand-held
devices. Also, their redundancy does not need to be fixed in advance and any number of
encoded symbols can be generated on the fly. Reference picture selection is used to limit
the effect of spatio-temporal error propagation. Limiting the effect of spatio-temporal
error propagation results in better video quality. Cross layer optimization is used to
minimize the data loss at the application layer when data is lost at the data link layer.
Experimental results on a High Speed Packet Access (HSPA) network simulator for
H.264 compressed standard video sequences show that the proposed technique achieves
significant Peak Signal to Noise Ratio (PSNR) and Percentage Degraded Video Duration
(PDVD) improvements over a state of the art error resilience technique known as
Interactive Error Control (IEC), which is a combination of Error Tracking and feedback
based Reference Picture Selection. The improvement is obtained at a cost of higher
end-to-end delay.
The proposed technique is improved by making the FEC (Rateless code) redundancy
channel adaptive. Automatic Repeat Request (ARQ) is used to adjust the redundancy
of the Rateless codes according to the channel conditions. Experimental results show
that the channel adaptive scheme achieves significant PSNR and PDVD improvements
over the static scheme for a simulated Long Term Evolution (LTE) network.
In the third part of the thesis, the performance of the previous two schemes is
improved by making the transmitter predict when rateless decoding will fail. In this
case, reference picture selection is invoked early and transmission of encoded symbols
for that source block is aborted. Simulations for an LTE network show that this results
in video quality improvement and bandwidth savings.
In the last part of the thesis, the performance of the adaptive technique is improved
by exploiting the history of the wireless channel. In a Rayleigh fading wireless channel,
the RLC-PDU losses are correlated under certain conditions. This correlation is
exploited to adjust the redundancy of the Rateless code and results in higher Rateless
code decoding success rate and higher video quality. Simulations for an LTE network
show that the improvement was significant when the packet loss rate in the two wireless
links was 10%.
To facilitate the implementation of the proposed error resilience techniques in practical
scenarios, RTP/UDP/IP level packetization schemes are also proposed for each
error resilience technique.
Compared to existing work, the proposed error resilience techniques provide better
video quality. Also, more emphasis is given to implementation issues in 3G networks
Recommended from our members
Time-frequency analysis based on split spectrum applied to audio and ultrasonic signals
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonSignal processing is a large subject with applications integral to a number of technological fields such as communication, audio, Voice over IP (VoIP), pattern recognition, sonar, radar, ultrasound and medical imaging. Techniques exist for the analysis, modelling, extraction, recognition and synthesis of signals of interest. The focus of this thesis is signal processing for acoustics (both sonic and ultrasonic). In the applications examined, signals of interest are usually incomplete, distorted and/or noisy. Therefore, reconstructing the signal, noise reduction and removal of any distortion/interference are the main goals of the signal processing techniques presented. The primary aim is to study and develop an advanced time-frequency signal processing technique for acoustic applications to enhance the quality of the signals. In the first part of the thesis, a technique is presented that models and maintains the correlation between temporal and spectral parameters of audio signals. A novel Packet Loss Concealment (PLC) method is developed with applications to VoIP, audio broadcasting, and streaming. The problem of modelling the time-varying frequency spectrum in the context of PLC is addressed, and a novel solution is proposed for tracking and using the temporal motion of spectral flow to reconstruct the signal. The proposed method utilises a Time-Frequency Motion (TFM) matrix representation of the audio signal, where each frequency is tagged with a motion vector estimate that is assessed by cross-correlation of the movement of spectral energy within sub-bands across time frames. The missing packets are estimated using extrapolation or interpolation algorithms using a TFM matrix and then inverse transformed to the time-domain for reconstruction of the signal. The proposed method is compared with conventional approaches using objective Performance Evaluation of Speech Quality (PESQ), and subjective Mean Opinion Scores (MOS) in a range of packet loss from 5% to 20%. The evaluation results demonstrate that the proposed algorithm substantially improves performance by an average of 2.85% and 5.9% in terms of PESQ and MOS respectively. In the second part of the thesis, the proposed method is extended and modified to address challenges of excessive coherent noise arising from ultrasonic signals gathered during Guided Wave Testing (GWT). It is an advanced Non-destructive testing technique which is used over several branches of industry to inspect large structures for defects where the structural integrity is of concern. In such systems, signal interpretation can often be challenging due to the multi-modal and dispersive propagation of Ultrasonic Guided Waves (UGWs). The multi-modal and dispersive nature of the received signals hampers the ability to detect defects in a given structure. The Split-Spectrum Processing (SSP) method with application for such signal has been studied and reviewed quantitatively to measure the enhancement in terms of Signal-to-Noise Ratio (SNR) and spatial resolution. In this thesis, the influence of SSP filter bank parameters on these signals is studied and optimised to improve SNR and spatial resolution considerably. The proposed method is compared analytically and experimentally with conventional approaches. The proposed SSP algorithm substantially improves SNR by an average of 30dB. The conclusions reached in this thesis will contribute to the progression of the GWT technique through considerable improvement in defect detection capability.Centre for Electronic Systems Research (CESR) of Brunel University London, The National Structural Integrity Research Centre (NSIRC) and TWI Ltd
Evaluating and improving the performance of video content distribution in lossy networks
The contributions in this research are split in to three distinct, but related, areas. The focus of the work is based on improving the efficiency of video content distribution in the networks that are liable to packet loss, such as the Internet. Initially, the benefits and limitations of content distribution using Forward Error Correction (FEC) in conjunction with the Transmission Control Protocol (TCP) is presented. Since added FEC can be used to reduce the number of retransmissions, the requirement for TCP to deal with any losses is greatly reduced. When real-time applications are needed, delay must be kept to a minimum, and retransmissions not desirable. A balance, therefore, between additional bandwidth and delays due to retransmissions must be struck. This is followed by the proposal of a hybrid transport, specifically for H.264 encoded video, as a compromise between the delay-prone TCP and the loss-prone UDP. It is argued that the playback quality at the receiver often need not be 100% perfect, providing a certain level is assured. Reliable TCP is used to transmit and guarantee delivery of the most important packets. The delay associated with the proposal is measured, and the potential for use as an alternative to the conventional methods of transporting video by either TCP or UDP alone is demonstrated. Finally, a new objective measurement is investigated for assessing the playback quality of video transported using TCP. A new metric is defined to characterise the quality of playback in terms of its continuity. Using packet traces generated from real TCP connections in a lossy environment, simulating the playback of a video is possible, whilst monitoring buffer behaviour to calculate pause intensity values. Subjective tests are conducted to verify the effectiveness of the metric introduced and show that the results of objective and subjective scores made are closely correlated
- âŠ