Bull, DR

Canagarajah, CN

Wang, D

English

This paper proposes a novel scheme for multiple description video coding approach using slice group coding tool proposed in H.264. Independent motion compensation loops are maintained for two descriptions in the encoder. In each description, one slice group is encoded as main information, while the other slice group is encoded very coarsely, as redundancy, to keep basic information. This coarse slice group can be encoded using normal encoding with coarse quantizer, or using predicted motion vectors by the main slice group. Mode decision is made to select best encoding method. Results show that our scheme works very well and keeps subjective quality very good for middle and higher bitrate. Redundancy and side quality can be controlled by changing parameters of coarsely coded slice group, unlike some other MDC methods with fixed redundancy. ©2004 IEEE.This paper proposes a novel scheme for multiple description video coding approach using slice group coding tool proposed in H.264. Independent motion compensation loops are maintained for two descriptions in the encoder. In each description, one slice group is encoded as main information, while the other slice group is encoded very coarsely, as redundancy, to keep basic information. This coarse slice group can be encoded using normal encoding with coarse quantizer, or using predicted motion vectors by the main slice group. Mode decision is made to select best encoding method. Results show that our scheme works very well and keeps subjective quality very good for middle and higher bitrate. Redundancy and side quality can be controlled by changing parameters of coarsely coded slice group, unlike some other MDC methods with fixed redundancy

Explore Bristol Research

                          Wang, D., Canagarajah, C. N., & Bull, D. R. (2004). Slice group basedmultiple description video coding using motion vector estimation. In 2004International Conference on Image Processing (ICIP 2004) Singapore. (Vol.5, pp. 3237 - 3240). Institute of Electrical and Electronics Engineers (IEEE).10.1109/ICIP.2004.1421803Link to published version (if available):10.1109/ICIP.2004.1421803Link to publication record in Explore Bristol ResearchPDF-documentUniversity of Bristol - Explore Bristol ResearchGeneral rightsThis document is made available in accordance with publisher policies. Please cite only the publishedversion using the reference above. Full terms of use are available:http://www.bristol.ac.uk/pure/about/ebr-terms.htmlTake down policyExplore Bristol Research is a digital archive and the intention is that deposited content should not beremoved. However, if you believe that this version of the work breaches copyright law please contactopen-access@bristol.ac.uk and include the following information in your message:• Your contact details• Bibliographic details for the item, including a URL• An outline of the nature of the complaintOn receipt of your message the Open Access Team will immediately investigate your claim, make aninitial judgement of the validity of the claim and, where appropriate, withdraw the item in questionfrom public view.2004 International Conference on Image Processing ( U P )  SLICE GROUP BASED MULTIPLE DESCRIPTION VIDEO CODING USING MOTION VECTOR ESTIMATION D. Wungt, N. Cunugurujuh and D. Bull Centre for Communications Research, University ofBristol, Bristol, BS8 IUB, UK Tel: +44 (0)I 17 9545202, Fax: +44 (0)I 17 9545206 'Email: Dong.Wang@!bristol.ac.uk ABSTRACT This paper proposes a novel scheme for multiple description video coding approach using slice group coding tool proposed in H.264. Independent motion compcnsation loops are maintained for two descriptions in  the encoder. In each description, one slicc group is encoded as main information, while the other slice group is  encoded very coarsely, as redundancy. to keep basic information. This coarse slice group can be encoded using normal encoding with coarse quantizer, or using predicted motion vectors by the main slice gwup. Mode decision is  made to select best encoding method. Results show that our scheme works very well and keeps subjective quality very good for middle and higher bitrate. Redundancy and side quality can be controlled by changing parameters o f  coarsely coded slice group, unlike some othcr MDC methods with fixed redundancy. 1. INTRODUCTION Video transmission over lossy network is  a challenging problem. In vidco compression, due to prcdictivc coding, any bit loss may cause great quality degradation. Multiple description coding is one approach to address this problem, where several sub bit strcams called descriptions are generated from source video. Each description can reconstruct video o f  acceptable quality and all the descriptions together can reconstmct higher quality video. Unlike layered video coding techniques, each description generated by MDC can independently be decoded and reconstructed to acceptable quality. This can give a gnceful degradation o f  received video with loss, while avoiding catastrophic failure oflayercd coding due to loss ofbase layer. A n  MDC system consists o f  two kinds of decoders. One is the central decoder which is  used when all the descriptions are received, and the other is  side decoder which just uscs one or a subset ofdescriptions to reconstruct video of acceptible quality More correlations in descriptions w i l l  result in higher quality o f  side decoded video. At the same time central decoder must perform with lower efficiency because more redundancy is  introduced. Extensive research on M D C  to increase the efficiency has been conducted. M D C  based on Scalar Quantization is  developed in [ I ]  to divide a signal by two coarser quantizers, and it's applied to predictive video coding in [2]. Output o f  each quantizer is  the approximation of  single description. Any one description can use 0-7803-8554-3/04/$20.00 02004 IEEE. its coarse data to generate a basic video and both ofthem can be combined to reconstmct higher quality video. Another approach on image coding is  addressed in [3] and [4] using painvise correlating transforms to transform a vcctor of DCT coefficients into another vector o f  correlated components, which introduces additional redundancy bctween components. This was used in  motion compensated video coding [5] .  Another simple way o f  generating MDC i s  that through pre- and post- processing. 3s in [6] .  Redundancy is  introduced by padding zeros in frequency domain. The source video frames arc transformed using DCT. Certain number o f  zeros are padded in frequency domain, and after inverse transform, the video is  sub-sampled into two descriptions. The two descriptions are independently coded at the encoder. In [7) ,  video sequence is  divided into two by mcans of odd and even frames and different conccalment methods are used to estimate lost frames. In [SI odd and even frames compose two descriptions, which i s  similar to [7], but three M C  loops are maintained. It perfoms well on ideal M D C  environments and packet lossy network. Arestriction is that i t  can only use previous two frames with constant weights of two motion vectors. Overlapping technique i s  used on motion vectors in [9] to achieve more accurate prediction o f  lost data. We propose a new method, with two descriptions, based on slice group (SG-MDC), the ncw coding tools developed in H.264. In each description. one slice group is encoded normally as main information, while the other slice group is  encoded very coarsely, as redundancy. to keep bmic information. Two descriptions are symmetric. To make this redundancy coding less costly, motion vector estimation technique is  used and additional coding optimization is  made between this technique and the normal encoding. The proposed scheme is  able to encode with little redundancy, which can varics by changing the quality of the redundancy slice group. The rest of this paper i s  organized as follows. In Section 2 our slice group based MDC is described. Section 3 gives the results and analysis of experiments. Conclusions are presented in section 4. 2. DESCRIPTION OF THE PROPOSED SG-MDC Slice Group is  a new coding tool in H.264. Picture is  dividcd into slice groups and i t  can be further divided into slices in scan order. Not like slice, slice group allows encoding picNre not by scan order which makc i t  much more flexible. There are totally 7 types of macroblock allocation for slice group, i.e. slice group 3237 Authorized licensed use limited to: UNIVERSITY OF BRISTOL. Downloaded on March 2, 2009 at 10:41 from IEEE Xplore.  Restrictions apply.Fig. I Macroblock Map For Dispersed Slice Group Fig. 3 Mode decision for SCB encoding n"'"fl Fig. 4 Motion Vector Estimation .......................................... r.._.~...-...~~.. 1; Dgaiptan 2 ).......--.....~...-.....-...-...........~ Fig. 2 Structure of proposed SG-MDC map types, in the current H.264 dnfts in which type 1 is called 'dispersed' slice group map. For two slice groups A and 8, macroblock map is as fig. 1. They are distributed as checkerboard, which is very effective for error concealment, and this map type with two slice groups is chosen as the basis of our MDC schcme. In our scheme, each slice group composes main information in one dcscription. z depicted in fig. 2. We call this slice group as main slice group. For each picture, the main slice group is encoded normally and the other slice group is also encoded. This slice group is completely redundancy, for it also exists in the other description as main slice group. The basic idea is to encode it using a big quantizer step size to keep basic information and try to make the redundancy as little as possible. If two descriptions are received correctly, the redundancy is discarded and using main information we can reconstruct video of good quality by standard decoder. If only one description is received, we can reconstmct main slice group of good quality, and use the redundancy to reconstluct the other slice group of acceptable quality by the side decoder. It is obvious that these two descriptions are symmetric and indcpendent fiom each other and any of them can reconstruct video without drift problem by itself. In the following we will only focus on the first description which uses slice group A(SGA) as main information, for the two descriptions are symmetric and we got the same performance out ofeach description. Encoding SGB can be made by encoding normally as SGA, but with a bigger quantizer step size (QP). We name it as normal encoding here. But results show that redundancy is too much, since motion and header information take up many bits in SGB. which is normally around 50%. For SGA is always encoded firstly which means we have SGAdata beforc encoding SGB, we employ motion vector (MV) estimation for SGB using the data of SGA, hereby reducing overhead for header and motion information. Howevcr, with the inaccurdtely estimated motion vectors which results in more bits for SCA, encoding will not be always optimal in spite of reducing bits for SGB hcader. If the costs are higher than normal encoding. there is no reason to use this estimation method. Based on this consideration, additional mode decision is made as fig. 3. We set the highest priority to skip mode. If thc result of mode decision in normal encoding is skip mode, we select skip mode. If not, encoding using MV estimation is compared to normal encoding. If the cost is lower than normal encoding, MV estimation based encoding is selected. Otherwise normal encoding is used instead. One bit in syntax should be used to flag this mode decision. if it is not skip mode. As to motion vector estimation. it is very flexible and lots of  estimation methods can bc used. The method indicated in fig. 4 is selectcd for our scheme. For dispersed slice group type, there are five macroblocks of which the middle one is for SGB, if the macroblock to be encoded in SGB is not the border or comer of picture. Each macroblock consists of 16 4x4 blocks. We estimate motion vecton for each block. At first, motion vectors of four blocks at the comer are estimated using four neighbour blocks in SCA. Then motion vectors of blocks at border of macroblock are estimated using neighbouring 3 blocks in SGA and one adjacent block at the comer. At last, the motion vectors of the four middle blocks are estimated using neighbouring 5 blocks. We use median methud to calculate the motion vector value. The reason we select 4x4 motion vectors is that generally 4x4 motion estimation is more accurate, and since we don't need to encode these motion vectors, it should be of the best performance. For border MB, similar median methods are used. Encoding of main slice group is completely normal encoding and can use multiple reference frames. This will make the encoding very efficient. Currently we use the most recent reference fnme for the redundancy slice group. The best motion vectors for each reference fnme in SGA will be generated during mode decision and we can use it directly without adding more 3238 Authorized licensed use limited to: UNIVERSITY OF BRISTOL. Downloaded on March 2, 2009 at 10:41 from IEEE Xplore.  Restrictions apply.38 3 6 ~  34- m' 0 3 2 ~ .  rr 5 30- a .  28 26 Padding MDC with QP=25 is at Bitrate= 785kbps and PSNR=31.4dB. . + + - Lineslmm np to bonom: QPA =25.21.29.31.33.35.37.39 For each lice UP8 vanes t which is far below his cum. { / 5 i f- QPB=43 26 QPBr32 to 51 , QPB=51 %OO 1050 1100 1150 1200 1250 Bitrate for one descnption (kbps) (b) computation. 3. RESULTS AND ANALYSIS We examine thc performance of our proposed SG-MDC. All the data are gat by assuming that one entire description is lost, which is  the ideal MDC environment. For a l l  the cases, we use thc video coding standard H.264 [ lO][l I] as the basic coder. H.264 is the latest video coding standard. It has many new features, which make it much bener than previous standards. Slice group coding tools make our scheme vcry convenient. Fixed frame rate (30frames/szcond) and constant quantizer step size are used for each dice in a11 frames of sequence. No B frame is  used. Entropy coding i s  CAVLC. Sequence 'paris' i s  used. Currently very few papers on MDC use H.264 as platform. We implement [ 6 ]  on H.264 for comparison, which is  called Padding MDC here. Central quality o f  SG-MDC is  presented in fig. 5 (a). Each line is one series o f  encoding with constant QP of SGA (QPA) and different QP o f  SGB (QPB). From tap to bosom QPA is  25 to 39. The several stars are the quality of normal single-description encoding using the samc QP as corrcsponding QPA. We can see that with the same QP, the central quality is  Redundancy of Encoding PARIS CIF 90, 29b 35 - 45 50 55 QP of Slice Group B (C) Fig. 5 Performance of SC-MDC. (a) Central Quality for different QPA with varying QPB; (b) Side Quality for QPA=25 with varying QPB; (c) Redundancy of different QPA with varying QPB. almost the same as that of single-description encoding, and with increasing o f  QPB, the central quality changes very slowly. which means changing side quality won't affect the quality of  SGA much (But with redundancy, the R(D) curve must be w m e  than the single-description encoding). Therefore, we can evaluate redundancy through increasing of bitratc with the same QP. Fig. 5 (b) gives an example o f  the property of side quality with changing QPB for ~onsfsnt QPA=25. We consider the bitnte o f  one description vs. Side PSNR. It's clear that with smaller QPB, thc side quality is better. With QPB increasing, the side quality and bitrate are lower. But when the QPB is very big, which means the quality o f  SGB i s  too low, the side quality keeps decrcasing but the bitnte increases. This is  because the prediction of SGA is too bad due to the very bad quality of SCE in previous frames and cncoding is  much less efficient. This properly results in a minimum point for the bitnte and a turning point for the R(D) curve. This can also bc seen in Fig. 5 (c). in which the redundancy cuwe is  similar as the R(D) curve in Fig. 5 (b). In order to see the details of the curve in this figure we haven't draw the Padding MDC, for which the point is  at 1570kbps and 31.4dB. which is  far below our curve. In fig. 5 (c) the redundancy curves are presented for different QPA. Each line is  for a constant QPA and varying QPB. For high quality video such as QPA being around 25, the redundancy is very small and minimum point is  23.1%. And for low bit rate, the redundancy i s  around 40%. Also due to the property of central quality described above, we can change the side quality by changing redundancy through varying QPB without affecting central quality. We can SKK that redundancy is higher far bigger QPA, which means that SG-MDC is more suitable for higher quality video. With higher QPA, the difference between QPA and QPB is  smaller and slice group B takes more percentage of  bits in the bitstream which results in more redundancy. And for big QP such 39, we can see that there is no minimum point for redundancy due to this small difference. For 3239 Authorized licensed use limited to: UNIVERSITY OF BRISTOL. Downloaded on March 2, 2009 at 10:41 from IEEE Xplore.  Restrictions apply.the Padding MDC, the property of redundancy is opposite to SG MDC. It’s high for high quality video and lower for low bit rate. From the comparison, it’s obvious that SG MDC is better than Padding MDC. At middle and higher bitrate. its redundancy is much higher than SG MDC, and with low bitrate it pcrforms just similar as SG MDC. Moreover, Padding MDC is fixed redundancy, i.e. side quality, while SG MDC can vary side quality. Fig. 6 shows B comparison of pictures of frame number 82 in pori.s sequence. The first one is the decoded frame using normal single-description encoding. The second one is the side decoded frame with only half rate received. The side quality is 27dB. but the subjective quality is sti l l  acceptable. This MDC mcthod doesn’t work so good for the sequences with much motion such as foreman sequence. This is due to the inaccurate motion vector estimations. Better estimation methods may improve the accuracy further. Nonlinear interpolation techniqucs can also be used, for there are many motion vectors available in thc neighbouring macroblacks. Moreover, currently we only use thc most recent reference frame for redundant slice group. Results are expcctcd to be better if we select reference according to reference frame numbers of neighbouring macroblocks. 4. CONCLUSIONS In this paper we introduced a novel MDC approach based on slice group coding tools in H.264. Two slice groups are used of which each composes main information for one description. Two independent MC loops are maintained which is well suited for ideal MDC environments. We add redundancy by encoding the other slice group coarsely and with motion vector estimation. It is shown through simulations that our SG-MDC performs very well especially for high quality video. REFERENCES V. Vaishampayan, “Design of multiple description scalar quantizers,” IEEE Trans. On infarmation Theory, vol. 39, no.3, pp.821-834, May 1993. V. Vaishampayan and S. John, “Interframe balanced-multiple-description video compression,” Packet Video ’99, New York, NY, USA, Apr. 1999. M. Orchard, Y. Wang. V. Vaishampayan, and A. Reibman, “Redundancy rate distortion analysis of multiple description coding using painvise correlating transforms,” Proc. IEEE Int. Conf. Image Proc, Santa Barbara, CA, USA, Oct. 1997. Y. Wang, M. Orchard, and A. Reibman. “Optimal pairwise correlating transforms for multiple description coding,’: Proc. IEEE Lnt. Conf Image Proc, Chicago, Illinois, USA, Oct. 1998. A. Reibman, H. Jafakhani, Y. Wang, and M. Orchard “Multiple description coding for video using motion compensated prediction,” Proc. IEEE lot. Conf. Image Proc, Kobe, Japan, Oct. 1999. D. Wang, N. Canaganjah, D. Redmill, D. Bull, “Multiple Descriptoin Video Coding Bascd on Zero Padding,” Proc. IEEE Int. Symposium on Circuits and Systems, Vancouver, Canada, May 2004. J. G Apostolopoulos, “Error-resilient video compression Normal Encoding with QP=25 PSNR=38dB Redundancy=ZS% Side PSNR=27dB Half rate received Fig. 6 Decoded Pictures of Frame no.82 through the use of multiple states,” Proc. lEEE Int. Conf. Image Proc, Vancouver, CA. USA, Sept. 2000. Y. Wang, S. Lin, “Error-Resilient Video Coding Using Multiple Description Motion Compensation,”, IEEE Trans. On Circuits and Systems for Video Technology, Vol.12, No.6, June 2002. C. -S. Kim and S. -U. Lee, “Multiple description motion coding algorithm for robust vidco transmission;’ IEEE Int. Symp. on Circuits and Syst., Geneva, Switzerland, May 2000. H.264 standard, JVT-G050, 7th meeting, Pattaya, Thailand, 7-14 March, 2003 . Thomas Wiegand, Gary I. Sullivan, Gisle Bjontegaard, and Ajay Luthra, “Overview of the H.2WAVC Video Coding Standard,” IEEE Transactions on Circuits and Systems for Video Technology, pp. 560- 576, July 2003. 3240 Authorized licensed use limited to: UNIVERSITY OF BRISTOL. Downloaded on March 2, 2009 at 10:41 from IEEE Xplore.  Restrictions apply.

Design of multiple description scalar quantizers,”

Interframe balanced-multiple-description video compression,” Packet Video ’99,

Multiple description coding for video using motion compensated prediction,”

Optimal pairwise correlating transforms for multiple description coding,’:

Redundancy rate distortion analysis of multiple description coding using painvise correlating transforms,”

Symposium on Circuits and Systems,

Slice group based multiple description video coding using motion vector estimation

https://research-information.bris.ac.uk/files/3015384/wang_IEEE_ICIP_2004.pdf

Slice group based multiple description video coding using motion vector estimation

Abstract

Similar works

Full text

Available Versions

Explore Bristol Research