Template based illumination compensation algorithm for multiview video coding

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1 Template based illumination compensation algorithm for multiview video coding Xiaoming Li* a, Lianlian Jiang b, Siwei Ma b, Debin Zhao a, Wen Gao b a Department of Computer Science and technology, Harbin Institute of Technology, Harbin China; b School of Electronic Engineering and Computer Science, Peking University, Beijing China ABSTRACT Recently multiview video coding (MVC) standard has been finalized as an extension of H.264/AVC by Joint Video Team (JVT). In the project Joint Multiview Video Model (JMVM) for the standardization, illumination compensation (IC) is adopted as a useful tool. In this paper, a novel illumination compensation algorithm based on template is proposed. The basic idea of the algorithm is that the illumination of the current block has a strong correlation with its adjacent template. Based on this idea, firstly a template based illumination compensation method is presented, and then a template models selection strategy is devised to improve the illumination compensation performance. The experimental results show that the proposed algorithm can improve the coding efficiency significantly. Keywords: Template, illumination compensation, H.264/AVC, multiview video coding 1. INTRODUCTION Multiview video is a group of video sequences captured by a set of cameras on different positions at the same time and from the same scene. It is much favored in the services such as free-viewpoint video (FVV), free-viewpoint television (FTV), and 3DTV [1], which expand the user s sensation far beyond what is offered by the traditional video. Multiview video coding has attracted great attention from industries and research institutes. Earlier in 1990s, MPEG-2 proposed multiview profile [2]. Besides, the ISO/IEC JTC1 Moving Pictures Experts Group (MPEG) has organized a group named 3DAV (3D Audio-Visual) [1], which is devoted to researching the technology of 3D audio and video in 2001 [3]. In the following years, there appear different types of international standards or representation formats. One of the practical and well-developed approaches is using multiple views to render a three-dimensional scene. The direct solution is to independently encode all the separated videos using a current video codec such as H.264/MPEG-4 AVC [4]. Due to containing a large amount of inter-view statistical dependencies, combined temporal/inter-view prediction should be exploited, referred to multiview video coding [5]. MVC specified by ISO/IEC ITU-T Rec. H.264 supports the direct coding of the synchronous information from multiple views using a single stream and exploits inter-camera redundancy to reduce the bit rate, which has been finalized in 2008 [6]. To improve the compression efficiency of multiview video coding, HHI proposes an H.264/AVC based multiview video coding scheme which has achieved much better performance compared to the simulcast coding [7] and has been selected as the reference model. The basic coding scheme in [8], as shown in Fig. 1, uses the hierarchical B prediction structure for each view. This scheme utilizes the correlation between frames at the same time point but different views for disparity estimation and compensation. In order to decrease the amount of data, removing redundancies among correlated pictures becomes the key issue. These redundancies can be classified into two types, inter-view similarity between adjacent camera views and temporal similarity between temporally successive images of the same view [9]. Motion compensation techniques that are well-developed for single-view video compression can be used to temporal prediction. Likewise, disparity compensation techniques can be utilized to reduce inter-view redundancies. The compensation process is fulfilled by block matching technique, generally aiming to find the best matching block in the reference frame, so that it contributions to minimum residual error after prediction. *xmli@jdl.ac.cn Visual Communications and Image Processing 2010, edited by Pascal Frossard, Houqiang Li, Feng Wu, Bernd Girod, Shipeng Li, Guo Wei, Proc. of SPIE Vol. 7744, SPIE CCC code: X/10/$18 doi: / Proc. of SPIE Vol

2 Figure 1. H.264/AVC-based MVC structure. However, there also exists illumination change between two views and can be classified into two categories: the global illumination change, which is caused by different calibrations between cameras, and the local illumination change, which is caused by the different angles and positions of the cameras. The reason why the problem has to be dealt with is that it may influence the accuracy of the disparity estimation and compensation. Then the amount of residual energy for the best match candidate will be increased. Furthermore, the searching process for best matching block and the disparity vector will be affected. Both of those further results in decreasing the coding efficiency. Later on, some algorithms have been proposed to compensate the illumination change. Global brightness-variation compensation scheme is proposed to improve the coding efficiency for video scenes that contain global brightness variations caused by fade in/out, camera-iris adjustment, flicker, illumination change, and so on [10]. Moreover, fast local motion-compensation algorithms improve motion-compensation performance for video sequences with brightness variations [11, 12]. On the whole, those algorithms use two factors for image intensity to robustly estimate and compensate namely the scale and offset. In order to calculate these factors, the least square method or the variance of mean values will have to be previously computed. In [11], the 2-D Lloyd max algorithm is also used to efficiently represent the scale and offset factors. It is due to high complexity and excessively computational time that these algorithms are hard to be adopted into MVC, especially while achieving relatively low coding efficiency. In [13], an adaptive local illumination change compensation method is brought forward with better achievement. In Joint Multiview Video Model, this method is adopted as a useful coding tool on top of the MVC features. Fundamentally, the proposed illumination change compensation method is based on a hybrid video coding structure. Since the DC component of the residual coefficient has strong relationship with the local illumination change, the method is implemented adaptively by coding this component of a macroblock previously. Then the proposed encoder performs the displacement vector estimation adopting MB-based illumination change compensation and encodes the difference value of the illumination change, namely offset factor. [14] applies a histogram matching algorithm for illumination compensation in the prefiltering step. It utilizes the distorted sequence to calculate a mapping function, and then all other camera views are corrected by this function to fit the chosen reference view. This algorithm obtains gains for both luminance component and chrominance component. What s more, a very popular approach called template matching prediction [15] uses template based texture synthesis for signal prediction, combined with regular directional prediction. For lack of the ability in synthesizing picture data with non-uniform illumination characteristics, a new template matching technique [16] with locally adaptive illumination compensation is proposed, based on a linear compensation model with scaling and offset parameters to compensate contrast and brightness disparities respectively. In this paper, we presented a template based illumination compensation (TBIC) algorithm for MVC. The basic idea is that the illumination of the current block has a strong correlation with its adjacent template. Consequently, the illumination change of the current block can be derived from the illumination change of the template. The innovation of this algorithm is that local illumination change is calculated by the template and compensated without additional bits transmission. The rest of the paper is organized as follows. Section 2 presents the template based illumination compensation algorithm for MVC. In the proposed approach, first, the detail of illumination compensation based on the Proc. of SPIE Vol

3 template is given. Second, a template models selection approach is presented for more accurate compensation. Section 3 provides the experimental results. The conclusions are given in the last section. 2. TEMPLATE BASED ILLUMINATION COMPENSATION Generally, illumination compensation is utilized to decrease the influence of illumination variation, and is usually implemented by subtracting the difference, named local illumination change, between the current block and the reference block when performing disparity compensation. The reconstructed block with IC mode is calculated as follow [6]: I( xy, ) Rxy (, ) rx ( d, y d) C (1) where I(x, y) is the reconstructed illumination value, R(x, y) means the quantized illumination residual signal, r(x+d x, y+d y ) is the prediction value of illumination, and C represents the value of IC. Therefore, the key issue of illumination compensation is the acquisition of C when reconstructing a block. To tackle this problem, template based illumination compensation algorithm is proposed. 2.1 Template based illumination compensation In this subsection, the detail of template based illumination compensation is presented. The template is defined as the reconstructed neighboring region (left and above) of the current block, as shown in Fig. 2. As we know, the illumination usually has spatial continuity; thus it can be assumed that the illumination of current block has strong correlation with its template. Similarly, the reference block and its corresponding template also have this correlation. Following this assumption, we give the basic idea of TBIC: estimating the illumination change between the current block and the reference block from the change between their templates, which is: x y C( B, B ) C( T, T ) (2) c r c r where B c, B r, T c and T r are the illumination value matrixes of the current block, the reference block, the template of the current block and the template of the reference block, and C is defined as (1). In this paper, we define that the illumination change between blocks B c and B r as the difference between the weighted summation of the illumination value of the pixels in template T c and that of the pixels in T r, which is: T C( B, B ) WT WT T c r c c r r where W c and W r are the illumination change weight matrixes. Then a virtual reference block can be constructed for accuracy disparity estimation and compensation: T T B ' B ( WT WT ) (4) r ( x, y) r( x, y) c c r r (3) Figure 2. The disparity estimation with template. Proc. of SPIE Vol

4 2.2 Template model selection method for TBIC In this subsection, the design of the weight matrixes which are used previously in (3) is described in detail. The idea of weight matrixes calculation is that some weight matrixes, namely candidate template models set, are given previously, and the optimal model is selected by a selection strategy presented in the follow. For example, in this paper, the candidate template models set are obtained according to the texture direction. For pixel p in the template, as shown in Fig. 3, at a texture direction, angle, this pixel has a projection length l p in the block, which is defined as the value of the correlation of pixel p to this block at direction. At the direction, a candidate weight matrix, or template model, can be obtained by normalizing the value of the correlation of all the pixels in the template, which is: where m is the number of pixels in the template. l,0 l,1 l, m 1 W (,,..., ), (5) m 1 m 1 m 1 l l l, i, i,i i 0 i 0 i 0 Figure 3. Representation of the correlation of a pixel to the block. Then, by the candidate template models and the template of the reference block, the optimal template model W for the reference block is selected as the illumination compensation weights W, which is calculated as: s t T arg min B W T. (6) x 0 y 0 where s and t are the width and the height of block B r respectively, and in this paper, { k /10 k 0,1, 2,...,9}. As the current block usually has the similar texture characteristic with the reference block, the template model W c can be set to W r too. r( x, y) 3. EXPERIMENTAL RESULTS In this section, we evaluate the proposed template based illumination compensation. Our algorithm is integrated with the reference software JMVM [17], and the experimental results on test sequence race1 (640x480), exit (640x480) and flamenco2 (640x480) are given in terms of rate-distortion curves. The testing configuration is shown in Table I. In this paper, we performed our algorithm on 16x16 mode as an additional mode, and multipass encoding was used for RDO. Fig. 4 presents the statistical results of our approach. The 12th frames at S0 and S1 in Fig. 1 are used for comparison as the reference frame and the current frame respectively, as shown in Fig. 4 (a) and (b). Fig. 4 (c) depicts the positions of blocks coded as TBIC mode within the 12th frame at S1 of race1. The marked macroblocks represent the macroblocks that are coded by our proposed TBIC mode. The result depicted in Fig.4 (c) is under QP equal to 28. In this case, the percentage of TBIC is about 60%. r Proc. of SPIE Vol

5 TABLE I Configuration for the Experiments Entropy Coding CABAC 8x8 transform on FME on Hadamard Transform on Search Range 32 ICMode off MotionSkipMode off SingleLoopDecoding off LoopFilterDisable on Fig. 4 (d) and (e) are the disparity vector fields of 12th frame at S1 by disparity estimation without TBIC and with TBIC respectively. It can be seen that the field in (e) is smoother than that in (d). As we know, the disparity is caused by the different camera positions, and at the same time instance, the disparity is inversely proportional to the depth of the object [18]. As a result, the disparity vector field should be smooth because of the continuity of the depth of objects. Then it can be concluded that the disparity vector by the disparity estimation with TBIC is more like the true disparity of the two scenes and coding performance can be improved by the disparity compensation with TBIC. (a) (b) (c) Proc. of SPIE Vol

6 N' III 7/ i\ NI _i Nj 4/ 4 II _-t / (d) (e) Figure 4. Statistical results of the proposed algorithm. (a) The 12th frame at S0 of race1 in Fig. 1. (b) The 12th frame at S1 of race1 in Fig.1, which references (a). (c) The positions of blocks coded as TBIC mode in (b). (d) Disparity vector field by the disparity estimation without IC. (e) Disparity vector field by the disparity estimation with TBIC. Fig. 5 gives the average coding performance. From Fig. 5 (a) we can see that the proposed algorithm can reduce 5% bits for race1 and Fig. 5 (b) shows that average 6% bits gain can be achieved for flamenco2. However, for exit, bits can be decreased by less than 1% at the low bit rate. TBIC has more significant advantage in race1 and flamenco2 because these sequences have more illumination change compared to exit. (a) (b) Proc. of SPIE Vol

7 Figure 5. RD comparison results for TBIC. (a) For race1. (b) For flamenco2. (c) For exit. (c) 4. CONCLUSION This paper proposes a novel illumination compensation algorithm which is based on template. The basic idea is that the illumination of the current block has correlation with its adjacent template. Based on this idea, firstly a template based illumination compensation method is given, and then a template models selection approach for this method are presented to improve the performance of the illumination compensation. The experimental results show that this method can significantly improve the coding efficiency. In the future, more MVC characters such as depth information can be utilized to obtain more accuracy value of illumination change and furthermore, the corresponding deblocking filter should be also designed. 5. ACKNOWLEDGEMENT This work was supported in part by National Science Foundation ( ) and National Basic Research Program of China (973 Program, 2009CB320905). REFERENCES 1. Report on 3DAV exploration, ISO/IEC JTC/SC29/WG11, N5878, July Generic coding of moving pictures and associated audio information-part 2: video, ITU-T Rec. H & ISO/IEC (MPEG 2 Systems), ITU-T and ISO/IEC JTC1 (1994). 3. M. Jose, MPEG 3DAV AhG activities report, 65th MPEG Meeting, Trondheim, Norway (2003). 4. Advance video coding for generic audio-visual services, ITU-T Recommendation H.264 & ISO/IEC AVC(2003) 5. S. Shinya, K. Hideaki and Y. Ohtani, Real-time free-viewer from multi-view video plus depth representation coded by H.264/AVC MVC extension, 3DTV Conference: The True Vision Capture, Transmission and Display of 3D Video, 1-6 (2009). 6. Ying Chen, Hannuksela, M. M., Ling Zhu, Hallapuro, A., Gabbouj, M., Houqiang Li, Coding techniques in multiview video coding and joint multiview video model, Picture Coding Symposium, May, Description of core experiments in MVC, ISO/IEC JTC1/SC29/WG11, MPEG2006/W7798, January H. Schwarz, D. Marpe, and T. Wiegand, Analysis of hierarchical B-pictures and MCTF, IEEE International Conference on Multimedia and Exposition (2006). 9. M. Flierl, A. Mavlankar, and B. Girod, Motion and disparity compensated coding for multi-view video, IEEE Transactions on Circuits and Systems for Video Technology (2007). 10. K. Kamikura, H. Watanabe, H. Jozawa, H. Kotera, and S. Ichinose, Global brightness variation compensation for video coding, IEEE Trans. Circuits Syst. Video Technol.,vol. 8, no. 12, pp , Dec S. H. Kim and R. H. Park, Fast local motion-compensation algorithm for video sequence with brightness variations, IEEE Trans. Circuits Syst. Video Technol., vol. 13, no. 4, pp , Apr Proc. of SPIE Vol

8 12. K. Sohn, Y. Kim, J. Seo, J. Yoon, G. Kim, C. Park, and J. Lee, Results on CE2 Using IBDE for Multi-View Video Coding, ISO/IEC JTC1/SC29/WG11, Klagenfurt, Austria, Doc. M13543, Jae-Ho Hur, Sukhee Cho, and Yung-Lyul Lee, Adaptive local illumination change compensation method for H.264/AVC-based multiview video coding, IEEE Trans. Circuits Syst. Video Technol., vol. 17., no. 11, pp , Nov Ulrich Fecker, Marcus Barkowsky, and Andre Kaup, Histogram-based prefiltering for luminance and chrominance compensation of multiview video, IEEE Trans. Circuits Syst. Video Technol., vol. 18., no. 9, pp , Nov Thiow Keng Tan, Choong Seng Boon, and Yoshinori Suzuki, Intra prediction by averaged template matching predictors, in CCNC. IEEE, Jan Yunfei Zheng, Peng Yin, Oscar Divorra Escoda, Xin Li and Cristian Gomila, Intra prediction using template matching with adaptive illumination compensation, IEEE International Conference on Image Processing, Joint multiview video model (JMVM) 8.0, JVT-AA207, Geneva, Switzerland, April X. Li, D. Zhao, S. Ma, W. Gao, Fast Disparity and Motion Estimation Based on correlations for Multiview Video Coding, IEEE Transactions on Consumer Electronics, vol. 54, No. 4, pp , Nov Proc. of SPIE Vol

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