Biomedical subjects

Aggelos K Katsaggelos

Publications and source records attributed to Aggelos K Katsaggelos.

9 recordsLinked to original sources

PubMed2006

Rate-distortion optimized hybrid error control for real-time packetized video transmission.

The problem of application-layer error control for real-time video transmission over packet lossy networks is commonly addressed via joint source-channel coding (JSCC), where source coding and forward error correction (FEC) are jointly designed to compensate for packet losses. In this paper, we consider hybrid application-layer error correction consisting of FEC and retransmissions. The study is carried out in an integrated joint source-channel coding (IJSCC) framework, where error resilient source coding, channel coding, and error concealment are jointly considered in order to achieve the best video delivery quality. We first show the advantage of the proposed IJSCC framework as compared to a sequential JSCC approach, where error resilient source coding and channel coding are not fully integrated. In the USCC framework, we also study the performance of different error control scenarios, such as pure FEC, pure retransmission, and their combination. Pure FEC and application layer retransmissions are shown to each achieve optimal results depending on the packet loss rates and the round-trip time. A hybrid of FEC and retransmissions is shown to outperform each component individually due to its greater flexibility.

Algorithms↗

PubMed2006

Stochastic methods for joint registration, restoration, and interpolation of multiple undersampled images.

Using a stochastic framework, we propose two algorithms for the problem of obtaining a single high-resolution image from multiple noisy, blurred, and undersampled images. The first is based on a Bayesian formulation that is implemented via the expectation maximization algorithm. The second is based on a maximum a posteriori formulation. In both of our formulations, the registration, noise, and image statistics are treated as unknown parameters. These unknown parameters and the high-resolution image are estimated jointly based on the available observations. We present an efficient implementation of these algorithms in the frequency domain that allows their application to large images. Simulations are presented that test and compare the proposed algorithms.

Algorithms↗

PubMed2006

VAPOR: variance-aware per-pixel optimal resource allocation.

Characterizing the video quality seen by an end-user is a critical component of any video transmission system. In packet-based communication systems, such as wireless channels or the Internet, packet delivery is not guaranteed. Therefore, from the point-of-view of the transmitter, the distortion at the receiver is a random variable. Traditional approaches have primarily focused on minimizing the expected value of the end-to-end distortion. This paper explores the benefits of accounting for not only the mean, but also the variance of the end-to-end distortion when allocating limited source and channel resources. By accounting for the variance of the distortion, the proposed approach increases the reliability of the system by making it more likely that what the end-user sees, closely resembles the mean end-to-end distortion calculated at the transmitter. Experimental results demonstrate that variance-aware resource allocation can help limit error propagation and is more robust to channel-mismatch than approaches whose goal is to strictly minimize the expected distortion.

Algorithms↗

PubMed2006

Motion compensated shape error concealment.

The introduction of Video Objects (VOs) is one of the innovations of MPEG-4. The alpha-plane of a VO defines its shape at a given instance in time and hence determines the boundary of its texture. In packet-based networks, shape, motion, and texture are subject to loss. While there has been considerable attention paid to the concealment of texture and motion errors, little has been done in the field of shape error concealment. In this paper we propose a post-processing shape error concealment technique that uses the motion compensated boundary information of the previously received alpha-plane. The proposed approach is based on matching received boundary segments in the current frame to the boundary in the previous frame. This matching is achieved by finding a maximally smooth motion vector field. After the current boundary segments are matched to the previous boundary, the missing boundary pieces are reconstructed by motion compensation. Experimental results demonstrating the performance of the proposed motion compensated shape error concealment method, and comparing it with the previously proposed weighted side matching method are presented.

Algorithms↗

PubMed2006

Joint source-channel coding for wireless object-based video communications utilizing data hiding.

In recent years, joint source-channel coding for multimedia communications has gained increased popularity. However, very limited work has been conducted to address the problem of joint source-channel coding for object-based video. In this paper, we propose a data hiding scheme that improves the error resilience of object-based video by adaptively embedding the shape and motion information into the texture data. Within a rate-distortion theoretical framework, the source coding, channel coding, data embedding, and decoder error concealment are jointly optimized based on knowledge of the transmission channel conditions. Our goal is to achieve the best video quality as expressed by the minimum total expected distortion. The optimization problem is solved using Lagrangian relaxation and dynamic programming. The performance of the proposed scheme is tested using simulations of a Rayleigh-fading wireless channel, and the algorithm is implemented based on the MPEG-4 verification model. Experimental results indicate that the proposed hybrid source-channel coding scheme significantly outperforms methods without data hiding or unequal error protection.

Algorithms↗

PubMed2005

Rate-distortion optimal video summary generation.

The need for video summarization originates primarily from a viewing time constraint. A shorter version of the original video sequence is desirable in a number of applications. Clearly, a shorter version is also necessary in applications where storage, communication bandwidth, and/or power are limited. The summarization process inevitably introduces distortion. The amount of summarization distortion is related to its "conciseness," or the number of frames available in the summary. If there are m frames in the original sequence and n frames in the summary, we define the summarization rate as m/n, to characterize this "conciseness". We also develop a new summarization distortion metric and formulate the summarization problem as a rate-distortion optimization problem. Optimal algorithms based on dynamic programming are presented and compared experimentally with heuristic algorithms. Practical constraints, like the maximum number of frames that can be skipped, are also considered in the formulation and solution of the problem.

Algorithms↗

PubMed2004

Spatially adaptive high-resolution image reconstruction of DCT-based compressed images.

The problem of recovering a high-resolution image from a sequence of low-resolution DCT-based compressed observations is considered in this paper. The introduction of compression complicates the recovery problem. We analyze the DCT quantization noise and propose to model it in the spatial domain as a colored Gaussian process. This allows us to estimate the quantization noise at low bit-rates without explicit knowledge of the original image frame, and we propose a method that simultaneously estimates the quantization noise along with the high-resolution data. We also incorporate a nonstationary image prior model to address blocking and ringing artifacts while still preserving edges. To facilitate the simultaneous estimate, we employ a regularization functional to determine the regularization parameter without any prior knowledge of the reconstruction procedure. The smoothing functional to be minimized is then formulated to have a global minimizer in spite of its nonlinearity by enforcing convergence and convexity requirements. Experiments illustrate the benefit of the proposed method when compared to traditional high-resolution image reconstruction methods. Quantitative and qualitative comparisons are provided.

Algorithms↗

PubMed2004

Shape error concealment using hermite splines.

The introduction of video objects (VOs) is one of the innovations of MPEG-4. The alpha-plane of a VO defines its shape at a given instance in time and hence determines the boundary of its texture. In packet-based networks, shape, motion, and texture are subject to loss. While there has been considerable attention paid to the concealment of texture and motion errors, little has been done in the field of shape error concealment. In this paper, we propose a post-processing shape error-concealment technique that uses geometric boundary information of the received alpha-plane. Second-order Hermite splines are used to model the received boundary in the neighboring blocks, while third order Hermite splines are used to model the missing boundary. The velocities of these splines are matched at the boundary point closest to the missing block. There exists the possibility of multiple concealing splines per group of lost boundary parts. Therefore, we draw every concealment spline combination that does not self-intersect and keep all possible results until the end. At the end, we select the concealment solution that results in one closed boundary. Experimental results demonstrating the performance of the proposed method and comparisons with prior proposed methods are presented.

Algorithms↗

PubMed2004

Bayesian resolution enhancement of compressed video.

Super-resolution algorithms recover high-frequency information from a sequence of low-resolution observations. In this paper, we consider the impact of video compression on the super-resolution task. Hybrid motion-compensation and transform coding schemes are the focus, as these methods provide observations of the underlying displacement values as well as a variable noise process. We utilize the Bayesian framework to incorporate this information and fuse the super-resolution and post-processing problems. A tractable solution is defined, and relationships between algorithm parameters and information in the compressed bitstream are established. The association between resolution recovery and compression ratio is also explored. Simulations illustrate the performance of the procedure with both synthetic and nonsynthetic sequences.

Algorithms↗