Symmetric distributed coding of stereo omnidirectional images

This paper presents a distributed coding scheme for the representation of 3D scenes captured by a pair of omnidirectional cameras with equivalent computational resources and transmission capabilities. The images are captured at different viewpoints and are encoded independently. A joint decoder exploits the correlation between images for improved decoding quality. The distributed coding is built on the multi-resolution representation of spherical images, whose information is split into two partitions. The encoder then transmits one partition after entropy coding, as well as the syndrome bits resulting from the channel encoding of the other partition. The joint decoder exploits the intra-view correlation by predicting one partition from the other partition. At the same time, it exploits the inter-view correlation using block-based disparity estimation between images from different cameras. Experiments demonstrate that the distributed coding solution performs better than a scheme where images are handled independently. Furthermore, the coding rate stays balanced between the different cameras, which permits to avoid hierarchical relations between vision sensors in camera networks.

[1]  D.J.C. MacKay,et al.  Good error-correcting codes based on very sparse matrices , 1997, Proceedings of IEEE International Symposium on Information Theory.

[2]  S. PradhanS.,et al.  Distributed source coding using syndromes (DISCUS) , 2006 .

[3]  Narendra Ahuja,et al.  Two-channel predictive multiple description coding , 2005, IEEE International Conference on Image Processing 2005.

[4]  Pascal Frossard,et al.  Distributed Coding of Spherical Images with Jointly Refined Decoding , 2005, 2005 IEEE 7th Workshop on Multimedia Signal Processing.

[5]  Sean S. B. Moore,et al.  FFTs for the 2-Sphere-Improvements and Variations , 1996 .

[6]  William Elwood Byerly,et al.  An elementary treatise on Fourier's series and spherical, cylindrical, and ellipsoidal harmonics, with applications to problems in mathematical physics , 2003 .

[7]  Ying Zhao,et al.  Compression of correlated binary sources using turbo codes , 2001, IEEE Communications Letters.

[8]  Radford M. Neal,et al.  Near Shannon limit performance of low density parity check codes , 1996 .

[9]  Jean-Pierre Antoine,et al.  Discrete Wavelet Frames on the sphere , 2004, 2004 12th European Signal Processing Conference.

[10]  S. Mallat A wavelet tour of signal processing , 1998 .

[11]  Bernd Girod,et al.  Distributed compression for large camera arrays , 2004, IEEE Workshop on Statistical Signal Processing, 2003.

[12]  Zixiang Xiong,et al.  Compression of binary sources with side information at the decoder using LDPC codes , 2002, IEEE Communications Letters.

[13]  Frans M. J. Willems Totally asynchronous Slepian-Wolf data compression , 1988, IEEE Trans. Inf. Theory.

[14]  Shigang Li,et al.  Spherical stereo for the construction of immersive VR environment , 2005, IEEE Proceedings. VR 2005. Virtual Reality, 2005..

[15]  Pascal Frossard,et al.  Distributed Coding of Multiresolution Omnidirectional Images , 2007, 2007 IEEE International Conference on Image Processing.

[16]  Pascal Frossard,et al.  Multiresolution motion estimation for omnidirectional images , 2005, 2005 13th European Signal Processing Conference.

[17]  Pier Luigi Dragotti,et al.  Distributed compression in camera sensor networks , 2004, IEEE 6th Workshop on Multimedia Signal Processing, 2004..

[18]  Kostas Daniilidis,et al.  Catadioptric Projective Geometry , 2001, International Journal of Computer Vision.

[19]  Zixiang Xiong,et al.  Design of Slepian-Wolf codes by channel code partitioning , 2004, Data Compression Conference, 2004. Proceedings. DCC 2004.

[20]  Kannan Ramchandran,et al.  PRISM: A Video Coding Paradigm With Motion Estimation at the Decoder , 2007, IEEE Transactions on Image Processing.

[21]  Zixiang Xiong,et al.  Layered Wyner–Ziv Video Coding , 2006, IEEE Transactions on Image Processing.

[22]  Pascal Frossard,et al.  Dense disparity estimation from omnidirectional images , 2007, 2007 IEEE Conference on Advanced Video and Signal Based Surveillance.

[23]  Enrico Magli,et al.  Distributed Arithmetic Coding , 2007, IEEE Communications Letters.

[24]  Aaron D. Wyner,et al.  The rate-distortion function for source coding with side information at the decoder , 1976, IEEE Trans. Inf. Theory.

[25]  R. L. Baker,et al.  Laplacian pyramid encoding: optimum rate and distortion allocations , 1989, International Conference on Acoustics, Speech, and Signal Processing,.

[26]  Bernd Girod,et al.  Distributed Video Coding , 2005, Proceedings of the IEEE.

[27]  Bernd Girod,et al.  Compression with side information using turbo codes , 2002, Proceedings DCC 2002. Data Compression Conference.

[28]  Edward H. Adelson,et al.  The Laplacian Pyramid as a Compact Image Code , 1983, IEEE Trans. Commun..

[29]  InverseSyndromeFormers PeiyuTan A Practical and Optimal Symmetric Slepian-Wolf Compression Strategy Using Syndrome Formers and Inverse Syndrome Formers , 2005 .

[30]  Kannan Ramchandran,et al.  Distributed source coding using syndromes (DISCUS): design and construction , 2003, IEEE Trans. Inf. Theory.

[31]  B. Girod,et al.  WYNER-ZIV CODING OF STEREO IMAGES WITH UNSUPERVISED LEARNING OF DISPARITY , 2007 .

[32]  Jack K. Wolf,et al.  Noiseless coding of correlated information sources , 1973, IEEE Trans. Inf. Theory.

[33]  Bernd Girod,et al.  Transform-domain Wyner-Ziv codec for video , 2004, IS&T/SPIE Electronic Imaging.

[34]  Michael S. Landy,et al.  Computational models of visual processing , 1991 .

[35]  Enrico Magli,et al.  Symmetric Distributed Arithmetic Coding of Correlated Sources , 2007, 2007 IEEE 9th Workshop on Multimedia Signal Processing.

[36]  Stphane Mallat,et al.  A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way , 2008 .

[37]  Christine Guillemot,et al.  Compressing the Laplacian Pyramid , 2006, 2006 IEEE Workshop on Multimedia Signal Processing.

[38]  Shlomo Shamai,et al.  Nested linear/Lattice codes for structured multiterminal binning , 2002, IEEE Trans. Inf. Theory.

[39]  Mina Sartipi,et al.  Distributed source coding in wireless sensor networks using LDPC coding: the entire Slepian-Wolf rate region , 2005, IEEE Wireless Communications and Networking Conference, 2005.

[40]  Qionghai Dai,et al.  Multi-View Images Coding Based on Multiterminal Source Coding , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[41]  Zixiang Xiong,et al.  Successive refinement for the Wyner-Ziv problem and layered code design , 2004, IEEE Transactions on Signal Processing.

[42]  Shree K. Nayar,et al.  A theory of catadioptric image formation , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[43]  Kannan Ramchandran,et al.  Distributed source coding: symmetric rates and applications to sensor networks , 2000, Proceedings DCC 2000. Data Compression Conference.

[44]  Pier Luigi Dragotti,et al.  Distributed Compression of Multi-View Images using a Geometrical Coding Approach , 2007, 2007 IEEE International Conference on Image Processing.