Consecutive corrupted MBs or slice errors are commonly seen in modern video transmission systems. Temporal error concealment is an effective approach to reduce the impact of errors. Conventional temporal error concealment techniques recover slice errors on a MB basis. We propose a new novel temporal scheme for slice error concealment based on a size-adaptive region basis. Size-adaptive region boundary matching can significantly reduce the misalignments or side mismatches that are commonly seen in MB-based approaches. Instead of using MSE or MAE as the matching criteria, We propose a matching criterion based on structural similarity (SSIM). Our proposed matching criterion can achieve better structural alignments and better visual perceptual quality. We also propose a method to detect motion vector outliers at the last stage of the error concealment scheme, which can further improve the visual quality of the concealed videos. Our proposed scheme conceals slice errors with good accuracy as well as low computation complexity, and it can be applied for real-time applications.

Video transmission over wireless networks suffers from packet loss due to either temporary packet drop or fading-induced bit errors. To ensure that the quality of the decoded video is not overly affected by the channel unreliability, the video applications have to provide sufficient robustness. In this paper, a novel slice interleaving algorithm is proposed for compressed video packetization. Each packet is constructed by interleaving independently decodable slices of the coded video bit-stream in a group of frames. We group slices into packets according to the maximum minimal distance of these slices. The scattered pattern guarantees that each lost slice has, as many as possible, spatial and temporal neighbors that belong to other correctly received packets. This scheme greatly strengthens the error concealment performance compared with traditional methods. Experimental results demonstrate the superiority of the proposed algorithm.

Video communication is often afflicted by packet loss over unreliable networks. To alleviate the quality degradation in the situation of packet loss, this paper proposes a novel error resilient slice interleaving method for compressed video packetization. Each packet is constructed by interleaving independently decodable slices of the coded video bit-stream in consecutive frames. The optimal interleaving pattern for minimizing the overall distortion of the decoded video, subject to a delay constraint, is determined based on the error concealment technique employed at the user end. Compared with traditional error-resilient methods, this scheme greatly improves the overall performance without requiring an increase in bit-rate. Experimental results on different video sequences demonstrate the effectiveness of the proposed approach.

With an empirically-derived complexity-rate-distortion model of a complexity scalable video encoder, we study the distributed optimization of several encoders sharing a wireless network, using the PSNR of the decoded video as the utility function. We will demonstrate how universal frequency reuse and source rate control can help the system degrade gracefully with increasing users, show the value of a simple pricing mechanism on transmission power in improving performance and study the effect of power allocation between transmitter and source encoder.

The H.264/AVC video coding standard encapsulates the most advanced video coding tools. Since the various techniques that lead to better coding efficiency of the coding standard also inevitably increase the complexity of the video encoder, real-time H.264 encoding of video streams is a challenging task. If available computational resource does not allow the entire encoding process to be carried out in time, a complexity scalable technique that ensures a graceful degradation of coding performance will be a valuable tool. We designed a video encoding scheme that allows the rate distortion (R-D) process to be carried out in a complexity scalable fashion. Our proposed singularly parameterized complexity scalable scheme allows the control of complexity-coding performance tradeoff when available resources are limited and the optimal R-D performance is unattainable.

In this paper, we introduce a singularly-parameterized complexity scalable H.264-compliant encoder. Through modeling its complexity-rate-distortion relationships, we derive optimized operating mode of the encoder (rate and complexity) and show through experiment that such optimization can help a video encoder operate within rate and time constraints. The design of the complexity scalable encoding scheme enables the encoder to perform optimization while taking into consideration the availability of computational resource. This extension of traditional rate-distortion optimization is necessary when time or power constraints do not allow a video encoder to achieve rate-distortion optimized coding performance. Our optimization scheme outputs parameters that allow the encoder to be as close to being rate-distortion optimized as possible, within rate and complexity constraints.

The H.264/AVC video coding standard encapsulates the most advanced video coding tools. The various techniques that lead to better coding efficiency of the coding standard also inevitably increase the complexity of the video encoder. Thus, real-time encoding of video streams with H.264 coding standard is a challenging task. If available computational resource does not allow the entire encoding process to be carried out in time, a complexity scalable technique that ensures a graceful degradation of coding performance will be a useful tool. This work proposes a singularly-parameterized complexity scalable rate-distortion framework for H.264/AVC encoders.

In this paper, a singularly parameterized complexity-scalable scheme is proposed for designing power-aware and power-adaptive H.264 video encoder. The proposed scheme enables adaptive control of the trade-off between the encoder's complexity and coding performance by dynamically updating a control parameter during encoding. This enables the encoder to perform optimally on a variety of computing platforms and runtime environments by adaption to instantaneous available computing resources and varying source video characteristics. The proposed scheme also allows computational resource allocation across layers in SVC encoders.

A novel segmentation-based image approximation and coding technique is proposed. A hybrid quad-binary (QB) tree structure is utilized to efficiently model and code geometrical information within images. Compared to other tree-based representation such as wedgelets, the proposed QB-tree based method is more efficient for a wide range of contour features such as junctions, corners and ridges, especially at low bit rates.

The paper describes a fast MPEG-2 to H.264 transcoder by leveraging the MPEG-2 metadata set to reduce the computational complexity of the H.264 encoding process. With the proposed fast transcoding algorithms, our software-based transcoder can perform real-time transcoding a MPEG-2 movie from a DVD disc (at D1 resolution and full frame-rate) and simultaneously performing RTP/UDP streaming of the H.264 video with AC-3 audio over IP networks using only a 1.6 GHz PC notebook. We can achieve about 20-30% faster than the full re-encoding method even at the same target bit-rate and without visible quality degradation. Benchmarking with existing software systems has shown similar results.

Temporal scalability in H.264/SVC video compression standard can be achieved with the hierarchical B-pictures (HB) structure. When performing motion estimation (ME) in the HB structure, the temporal distance between the current frame and reference frame(s) can be large (up to 32 frames apart). This limits the performance of fast search algorithm as larger search window is often necessary. Extensive experiments showed that popular fast suboptimal block ME algorithms are ineffective at tracking large motions across several frames. In this paper, we propose a new framework called Lacing which integrates well with any fast block ME techniques to significantly improve the motion prediction accuracy in quality of the motion-compensated frame and also result in smoother motion vector fields with lower entropy.

In signal approximation, classical wavelet synthesis are known to produce Gibbs-like phenomenon around discontinuities when wavelet coefficients in the cone of influence of the discontinuities are quantized. By analyzing a function in a piecewise manner, filtering across discontinuities can be avoided. Using this principle, the interval wavelet transform can generate sparser representations in the vicinity of discontinuities than classical wavelet transforms. This work introduces two new constructions of interval wavelets and shows how they can be used for image compression and upscaling.

This paper proposes a method for progressive lossy-to-lossless compression of four-dimensional (4-D) medical images (sequences of volumetric images over time) by using a combination of three-dimensional (3-D) integer wavelet transform (IWT) and 3-D motion compensation. A 3-D extension of the set-partitioning in hierarchical trees (SPIHT) algorithm is employed for coding the wavelet coefficients. To effectively exploit the redundancy between consecutive 3-D images, the concepts of key and residual frames from video coding is used. A fast 3-D cube matching algorithm is employed to do motion estimation. The key and the residual volumes are then coded using 3-D IWT and the modified 3-D SPIHT. The experimental results presented in this paper show that our proposed compression scheme achieves better lossy and lossless compression performance on 4-D medical images when compared with JPEG-2000 and volumetric compression based on 3-D SPIHT.

This paper describes a variation of the set partitioning in hierarchical trees (SPIHT) scheme for color image coding. By using partially linked spatial orientation tree structures across different spectral planes, the new color-SPIHT scheme is able to embed both chrominance and luminance data in the coded bit stream. The performance is comparable to that of a SPIHT-based coding scheme but with significantly lower computational complexity.