scispace - formally typeset
Proceedings ArticleDOI: 10.1109/ECS.2015.7124979

Improved motion compensation temporal filtering (MCTF) for Scalable Video coding (H.264/SVC) standards

01 Feb 2015-pp 602-606
Abstract: The newer of the ITU/MPEG standardization effort of H.264/AVC scalable extension, Joint Scalable Video Model (JSVM) has been made for efficient Scalable Video Coding (SVC). The Motion Estimation (ME) and Motion Compensation (MC) techniques are applied to exploit the redundancy between two consecutive frames. This paper deals with application of Multi-resolutional Discerete Wavelet Transform (DWT) to improve channel bandwidth aspects and the visual quality of the video in error prone network. A gradient based approach is used to recover the lost pixels via finding the direction of maximum amount of correctly received pixels and concoles the lost pixels. The algorithm applied in a temporal domain on the spatial frequency of the Motion Vectors (MV). To evaluate the proposed algorithm an open source reference software for SVC called Joint Scalable Video Model (JSVM) developed by ITU is used. In the results shows the proposed algorithm gets the significant improvement in visual quality for error prone networks with reduction in bandwidth & improves PSNR.

...read more

Topics: Scalable Video Coding (66%), Motion compensation (65%), Quarter-pixel motion (64%) ...read more
References
  More

Open accessBook
01 Sep 1998-
Abstract: Preface. Acknowledgments. 1. Continuous Wavelet Transform. Introduction. Continuous-Time Wavelets. Definition of the CWT. The CWT as a Correlation. Constant Q-Factor Filtering Interpretation and Time-Frequency Resolution. The CWT as an Operator. Inverse CWT. Problems. 2. Introduction to the Discrete Wavelet Transform and Orthogonal Wavelet Decomposition. Introduction. Approximations of Vectors in Nested Linear Vector Subspaces. Example of Approximating Vectors in Nested Subspaces of a Finite-Dimensional Linear Vector Space. Example of Approximating Vectors in Nested Subspaces of an Infinite-Dimensional Linear Vector Space. Example of an MRA. Bases for the Approximation Subspaces and Haar Scaling Function. Bases for the Detail Subspaces and Haar Wavelet. Digital Filter Implementation of the Haar Wavelet Decomposition. Problems. 3. MRA, Orthonormal Wavelets, and Their Relationship to Filter Banks. Introduction. Formal Definition of an MRA. Construction of a General Orthonormal MRA. Scaling Function and Subspaces. Implications of the Dilation Equation and Orthogonality. A Wavelet Basis for the MRA. Two-scale Relation for psi (t). Basis for the Detail Subspaces. Direct Sum Decomposition. Digital Filtering Interpretation. Decomposition Filters. Reconstructing the Signal. Examples of Orthogonal Basis-Generating Wavelets. Daubechies D4 Scaling Function and Wavelet. Bandlimited Wavelets. Interpreting Orthonormal MRAs for Discrete-Time Signals. Continuous-time MRA Interpretation for the DTWT. Discrete-Time MRA. Basis Functions for the DTWT. Miscellaneous Issues Related to PRQMF Filter Banks. Generating Scaling Functions and Wavelets from Filter Coefficients. Problems. 4. Alternative Wavelet Representations. Introduction. Biorthogonal Wavelet Bases. Filtering Relationship for Biorthogonal Filters. Examples of Biorthogonal Scaling Functions and Wavelets. Two-Dimensional Wavelets. Nonseparable Multidimensional Wavelets. Wavelet Packets. Problems. 5. Wavelet Transform and Data Compression. Introduction. Transform Coding. DTWT for Image Compression. Image Compression Using DTWT and Run-length Encoding. Embedded Tree Image Coding. Comparison with JPEG. Audio Compression. Audio Masking. Standards Specifying Subband Implementation: ISO/MPEG Coding for Audio. Wavelet-Based Audio Coding. Video Coding Using Multiresolution Techniques: A Brief Introduction. 6. Other Applications of Wavelet Transforms. Introduction. Wavelet Denoising. Speckle Removal. Edge Detection and Object Isolation. Image Fusion. Object Detection by Wavelet Transforms of Projections. Communication Applications. Scaling Functions as Signaling Pulses. Discrete Wavelet Multitone Modulation. 7. Advanced Topics. Introduction. CWTs Revisited. Parseval's Identity for the CWT. Inverse CWT Is a Many-to-One Operation. Wavelet Inner Product as a Projection Operation. Bridging the Gap Between CWTs and DWTs. CWT with an Orthonormal Basis-Generating Wavelet. A Trous Algorithm. Regularity and Convergence. Daubechies Construction of Orthonormal Scaling Functions. Bandlimited Biorthogonal Decomposition. Scaling Function Pair Construction. Wavelet Pair Construction. Design and Selection of Wavelets. The Lifting Scheme. Best Basis Selection. Wavelet Matching. Perfect Reconstruction Circular Convolution Filter Banks. Downsampling. Upsampling. Procedure for Implementation. Conditions for Perfect Reconstruction. Procedure for Constructing PRCC Filter Banks. Interpolators Matched to the Input Process. Interpolation Sampling. Frequency-Sampled Implementation of Bandlimited DWTs. The Scaling Operation and Self-Similar Signals. LTI Systems and Eigenfunctions. Continuous-Time Linear Scale-Invariant System. Scaling in Discrete Time. Discrete-time LSI Systems. Appendix A. Fundamentals of Multirate Systems. The Downsampler. The Upsampler. Noble Identities. Appendix B. Linear Algebra and Vector Spaces. Brief Review of Vector Spaces. Vector Subspace. Linear Independence and Bases. Inner Product Spaces. Hilbert Space and Riesz Bases. Index.

...read more

Topics: Biorthogonal wavelet (74%), Orthogonal wavelet (73%), Discrete wavelet transform (71%) ...read more

667 Citations


Open accessJournal ArticleDOI: 10.1016/J.IMAGE.2004.06.004
Abstract: Scalability at the bitstream level is an important feature for encoded video that is to be transmitted and stored with a variety of target rates or to be replayed on devices with different capabilities and resolutions. This is attractive for digital cinema applications, where the same encoded source representation could seamlessly be used for purposes of archival and various distribution channels. Conventional high-performance video compression schemes are based on the method of motion-compensated prediction, using a recursive loop in the prediction process. Due to this recursion and the inherent drift in cases of deviation between encoder and decoder states, scalability is difficult to realize and typically effects a penalty in compression performance for prediction-based coders. The method of interframe wavelet coding overcomes this limitation by replacing the prediction along the time axis by a wavelet filter, which can nevertheless be operated in combination with motion compensation. Recent advances in motion-compensated temporal filtering (MCTF) have proven that combination with arbitrary motion compensation methods is possible. Compression performance is achieved that is comparable with state of the art single-layer coders targeting only for one rate. The paper provides an explanation of MCTF methods and the resulting 3D wavelet representation, and shows results obtained in the context of encoding digital cinema (DC) materials.

...read more

Topics: Motion compensation (62%), Data compression (60%), Inter frame (56%) ...read more

127 Citations


Open accessJournal ArticleDOI: 10.1109/CSVT.2009.2017311
Yi Guo1, Ying Chen2, Ye-Kui Wang3, Houqiang Li1  +2 moreInstitutions (3)
Abstract: Scalable video coding (SVC), which is the scalable extension of the H.264/AVC standard, was developed by the Joint Video Team (JVT) of ISO/IEC MPEG (Moving Picture Experts Group) and ITU-T VCEG (Video Coding Experts Group). SVC is designed to provide adaptation capability for heterogeneous network structures and different receiving devices with the help of temporal, spatial, and quality scalabilities. It is challenging to achieve graceful quality degradation in an error-prone environment, since channel errors can drastically deteriorate the quality of the video. Error resilient coding and error concealment techniques have been introduced into SVC to reduce the quality degradation impact of transmission errors. Some of the techniques are inherited from or applicable also to H.264/AVC, while some of them take advantage of the SVC coding structure and coding tools. In this paper, the error resilient coding and error concealment tools in SVC are first reviewed. Then, several important tools such as loss-aware rate-distortion optimized macroblock mode decision algorithm and error concealment methods in SVC are discussed and experimental results are provided to show the benefits from them. The results demonstrate that PSNR gains can be achieved for the conventional inter prediction (IPPP) coding structure or the hierarchical bi-predictive (B) picture coding structure with large group of pictures size, for all the tested sequences and under various combinations of packet loss rates, compared with the basic joint scalable video model (JSVM) design applying no error resilient tools at the encoder and only picture copy error concealment method at the decoder.

...read more

Topics: Coding tree unit (67%), Scalable Video Coding (67%), Multiview Video Coding (63%) ...read more

68 Citations


Proceedings ArticleDOI: 10.1109/ISCAS.2008.4542206
Shujie Liu1, Ying Chen2, Ye-Kui Wang3, Moncef Gabbouj2  +2 moreInstitutions (3)
18 May 2008-
Abstract: The multiview video coding (MVC) standard is currently under development by the Joint Video Team as an extension of the advanced video coding (H.264/AVC) standard. An MVC encoder compresses more than one viewpoint of a scene captured by different cameras. Redundancies between views can be used for inter-view prediction in encoding as well as error concealment in decoding. In this paper, a new algorithm utilizing motion information of pictures from other views to conceal a lost picture is proposed. The algorithm first derives motion information for a lost picture based on motion fields of pictures in adjacent views. Then, traditional motion compensation is invoked within the view containing the lost picture to derive a concealed frame. Experimental results show that the proposed algorithm can improve video quality with a negligible computational complexity overhead compared to simple temporal error concealment algorithms.

...read more

Topics: Motion compensation (68%), Multiview Video Coding (66%), Video compression picture types (64%) ...read more

33 Citations


Journal ArticleDOI: 10.1109/TMM.2006.886339
Yu Wang1, Tao Fang1, Lap-Pui Chau1, Kim-Hui Yap1Institutions (1)
Abstract: The motion-compensated temporal filtering (MCTF)-based scalable video coding (SVC) provides a full scalability including spatial, temporal and signal-to-noise ratio (SNR) scalability with fine granularity, each of which may result in different visual effect. This paper addresses a novel approach of two-dimensional unequal error protection (2D UEP) for the scalable video with a combined temporal and quality (SNR) scalability over packet-erasure channel. The bit-stream is divided into scalable subbitstreams based on the structure of MCTF. Each subbitstream is further divided into several quality layers. Unequal quantities of bits are allocated to protect different layers to obtain acceptable quality video with smooth degradation under different transmission error conditions. Experimental results are presented to show the advantage of the proposed 2D UEP scheme over the traditional one-dimensional unequal error protection (1D UEP) scheme. Comparing the proposed method with the 1D UEP scheme on SNR layers, our method gives up to 0.81-dB improvement for some video sequences

...read more

25 Citations


Network Information
Related Papers (5)
01 Oct 2007

Jun-Ren Ding, Jar-Ferr Yang

01 Oct 2006

L. Xu, Sunil Kumar

27 May 2007

D. Athanasopoulos, Thanos Stouraitis