18,437 research outputs found
Multiple description video coding for stereoscopic 3D
In this paper, we propose an MDC schemes for stereoscopic 3D video. In the literature, MDC has previously been applied in 2D video but not so much in 3D video. The proposed algorithm enhances the error resilience of the 3D video using the combination of even and odd frame based MDC while retaining good temporal prediction efficiency for video over error-prone networks. Improvements are made to the original even and odd frame MDC scheme by adding a controllable amount of side information to improve frame interpolation at the decoder. The side information is also sent according to the video sequence motion for further improvement. The performance of the proposed algorithms is evaluated in error free and error prone environments especially for wireless channels. Simulation results show improved performance using the proposed MDC at high error rates compared to the single description coding (SDC) and the original even and odd frame MDC
Distributed Representation of Geometrically Correlated Images with Compressed Linear Measurements
This paper addresses the problem of distributed coding of images whose
correlation is driven by the motion of objects or positioning of the vision
sensors. It concentrates on the problem where images are encoded with
compressed linear measurements. We propose a geometry-based correlation model
in order to describe the common information in pairs of images. We assume that
the constitutive components of natural images can be captured by visual
features that undergo local transformations (e.g., translation) in different
images. We first identify prominent visual features by computing a sparse
approximation of a reference image with a dictionary of geometric basis
functions. We then pose a regularized optimization problem to estimate the
corresponding features in correlated images given by quantized linear
measurements. The estimated features have to comply with the compressed
information and to represent consistent transformation between images. The
correlation model is given by the relative geometric transformations between
corresponding features. We then propose an efficient joint decoding algorithm
that estimates the compressed images such that they stay consistent with both
the quantized measurements and the correlation model. Experimental results show
that the proposed algorithm effectively estimates the correlation between
images in multi-view datasets. In addition, the proposed algorithm provides
effective decoding performance that compares advantageously to independent
coding solutions as well as state-of-the-art distributed coding schemes based
on disparity learning
Source-Channel Diversity for Parallel Channels
We consider transmitting a source across a pair of independent, non-ergodic
channels with random states (e.g., slow fading channels) so as to minimize the
average distortion. The general problem is unsolved. Hence, we focus on
comparing two commonly used source and channel encoding systems which
correspond to exploiting diversity either at the physical layer through
parallel channel coding or at the application layer through multiple
description source coding.
For on-off channel models, source coding diversity offers better performance.
For channels with a continuous range of reception quality, we show the reverse
is true. Specifically, we introduce a new figure of merit called the distortion
exponent which measures how fast the average distortion decays with SNR. For
continuous-state models such as additive white Gaussian noise channels with
multiplicative Rayleigh fading, optimal channel coding diversity at the
physical layer is more efficient than source coding diversity at the
application layer in that the former achieves a better distortion exponent.
Finally, we consider a third decoding architecture: multiple description
encoding with a joint source-channel decoding. We show that this architecture
achieves the same distortion exponent as systems with optimal channel coding
diversity for continuous-state channels, and maintains the the advantages of
multiple description systems for on-off channels. Thus, the multiple
description system with joint decoding achieves the best performance, from
among the three architectures considered, on both continuous-state and on-off
channels.Comment: 48 pages, 14 figure
A robust coding scheme for packet video
We present a layered packet video coding algorithm based on a progressive transmission scheme. The algorithm provides good compression and can handle significant packet loss with graceful degradation in the reconstruction sequence. Simulation results for various conditions are presented
Feedforward data-aided phase noise estimation from a DCT basis expansion
This contribution deals with phase noise estimation from pilot symbols. The phase noise process is approximated by an expansion of discrete cosine transform (DCT) basis functions containing only a few terms. We propose a feedforward algorithm that estimates the DCT coefficients without requiring detailed knowledge about the phase noise statistics. We demonstrate that the resulting (linearized) mean-square phase estimation error consists of two contributions: a contribution from the additive noise, that equals the Cramer-Rao lower bound, and a noise independent contribution, that results front the phase noise modeling error. We investigate the effect of the symbol sequence length, the pilot symbol positions, the number of pilot symbols, and the number of estimated DCT coefficients it the estimation accuracy and on the corresponding bit error rate (PER). We propose a pilot symbol configuration allowing to estimate any number of DCT coefficients not exceeding the number of pilot Symbols, providing a considerable Performance improvement as compared to other pilot symbol configurations. For large block sizes, the DCT-based estimation algorithm substantially outperforms algorithms that estimate only the time-average or the linear trend of the carrier phase. Copyright (C) 2009 J. Bhatti and M. Moeneclaey
A robust coding scheme for packet video
A layered packet video coding algorithm based on a progressive transmission scheme is presented. The algorithm provides good compression and can handle significant packet loss with graceful degradation in the reconstruction sequence. Simulation results for various conditions are presented
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
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