An Efficient and Low-Delay Mctf Partitioning
01 Oct 2006-pp 1901-1904
TL;DR: A new low-delay motion compensated temporal filtering (MCTF) structure is proposed based on the residual energy computations, which outperforms the `low-delay MCTF' scheme suggested in the joint scalable video model (JSVM) in terms of delay, number of badly matched blocks and PSNR performance.
Abstract: In this paper, we compute the residual energy of predictive frames (i.e., unidirectional and bidirectional motion prediction) by using the autocorrelation between successive video frames at different frame lags (or prediction terms). A new low-delay motion compensated temporal filtering (MCTF) structure is proposed based on the residual energy computations, which outperforms the `low-delay MCTF' scheme suggested in the joint scalable video model (JSVM) in terms of delay, number of badly matched blocks and PSNR performance. The PSNR performance of the proposed scheme is only slightly lower than the `conventional 5/3 MCTF' scheme. This scheme can also be used with other types of wavelet filters (e.g., Haar) and can substitute the MCTF in 3D wavelet-based video codecs to achieve low delay with only minor reduction in coding efficiency.
References
More filters
27 Jun 2005
TL;DR: This paper gives a short overview over scalable video coding techniques and analyzes in more detail the encoder/decoder drift problem, which is the major reason why scalable coding has been significantly less efficient than single-layer coding in most of these implementations.
Abstract: Scalable video coding is attractive due to the capability of reconstructing lower resolution or lower quality signals from partial bit streams. This allows for simple solutions in adaptation to network and terminal capabilities. Different modalities of scalability are specified by video coding standards like MPEG-2 and MPEG-4. This paper gives a short overview over these techniques and analyzes in more detail the encoder/decoder drift problem, which is the major reason why scalable coding has been significantly less efficient than single-layer coding in most of these implementations. Only recently, new scalable video coding technology has evolved, which seems to close the gap of compression performance compared to state of the art single-layer video coding. New methods of efficient enhancement layer prediction were developed to improve traditional (motion-compensated hybrid) scalable coders, providing more flexible compromises on the drift problem. As a new technology trend, motion-compensated spatiotemporal wavelet coding has matured which entirely discards the drift and allows most flexible combinations of spatial, temporal, and signal-to-noise ratio (SNR) scalability with fine granularity over a broad range of data rates.
467 citations
TL;DR: This work derives the appropriate G that gives the desired correlation function p(k)=e/sup -/spl beta//spl radic/k/.
Abstract: Statistical evidence suggests that the autocorrelation function p(k) (k=0,1,...) of a compressed-video sequence is better captured by p(k)=e/sup -/spl beta//spl radic/k/ than by p(k)=k/sup -/spl beta//=e/sup -/spl beta/logk/ (long-range dependence) or p(k)=e/sup -/spl beta/k/ (Markovian). A video model with such a correlation structure is introduced based on the so-called M/G//spl infin/ input processes. In essence, the M/G//spl infin/ process is a stationary version of the busy-server process of a discrete-time M/G//spl infin/ queue. By varying G, many forms of time dependence can be displayed, which makes the class of M/G//spl infin/ input models a good candidate for modeling many types of correlated traffic in computer networks. For video traffic, we derive the appropriate G that gives the desired correlation function p(k)=e/sup -/spl beta//spl radic/k/. Though not Markovian, this model is shown to exhibit short-range dependence. Poisson variates of the M/G//spl infin/ model are appropriately transformed to capture the marginal distribution of a video sequence. Using the performance of a real video stream as a reference, we study via simulations the queueing performance under three video models: our M/G//spl infin/ model, the fractional ARIMA model (which exhibits LRD), and the DAR(1) model (which exhibits a Markovian structure). Our results indicate that only the M/G//spl infin/ model is capable of consistently providing acceptable predictions of the actual queueing performance. Furthermore, only O(n) computations are required to generate an M/G//spl infin/ trace of length n, compared to O(n/sup 2/) for an F-ARIMA trace.
195 citations
TL;DR: This paper introduces bidirectional motion compensated temporal filtering with unconnected pixel detection and I blocks and incorporates a recently suggested lifting implementation of the subband/wavelet filter for improved MV accuracy in an MC-EZBC coder.
Abstract: In conventional motion-compensated three-dimensional subband/wavelet coding, where the motion compensation is unidirectional, incorrect classification of connected and unconnected pixels caused by incorrect motion vectors (MVs) has resulted in some coding inefficiency and visual artifacts in the embedded low-frame-rate video. In this paper, we introduce bidirectional motion compensated temporal filtering with unconnected pixel detection and I blocks. We also incorporate a recently suggested lifting implementation of the subband/wavelet filter for improved MV accuracy in an MC-EZBC coder. Simulation results compare PSNR performance of this new version of MC-EZBC versus H.26L under the constraint of equal groups of pictures size, and show a general parity with this state-of-the-art nonscalable coder on several test clips.
182 citations
Book•
22 Nov 2021
TL;DR: Signals and Sampling, Signal Composition, Rendering and Presentation, Signal and Parameter Estimation, Feature Transforms and Classification, and Applications and Standards.
Abstract: 1 Introduction.- A: Multimedia Signal Processing and Analysis.- 2 Signals and Sampling.- 3 Statistical Analysis of Multimedia Signals.- 4 Linear Systems and Transforms.- 5 Pre- and Postprocessing.- B: Content-related Multimedia Signal Analysis.- 6 Perceptual Properties of Vision and Hearing.- 7 Features of Multimedia Signals.- 8 Signal and Parameter Estimation.- 9 Feature Transforms and Classification.- 10 Signal Decomposition.- C: Coding of Multimedia Signals.- 11 Quantization and Coding.- 12 Still Image Coding.- 13 Video Coding.- 14 Audio Coding.- D: Applications and Standards.- 15 Transmission and Storage.- 16 Signal Composition, Rendering and Presentation.- 17 Multimedia Representation Standards.- Appendices.- A Quality Measurement.- A.1 Signal Quality.- A.1.1 Objective Signal Quality Measurements.- A.1.2 Subjective Assessment.- A.2 Classification Quality.- B Vector and Matrix Algebra.- C Symbols and Variables.- D Acronyms.- References.
63 citations