Structure-based motion estimation for video compression

Motion estimation is a crucial process in video compression algorithms, aiming at reducing the temporal redundancy in video data. Traditional block-based motion estimation methods lead to satisfactory results in different situations but fail in others when dealing with high local structural variations. In this paper, a structure-based approach for motion estimation is proposed, taking into account structural information of the frames throughout the video sequence. Results show that using the proposed method, relevant local information can be better reconstructed comparing to the standard motion estimation approach, thus reducing the residual error, which may lead to improved rate-distortion performance of video compression algorithms.

[1]  J. Bigun,et al.  Optimal Orientation Detection of Linear Symmetry , 1987, ICCV 1987.

[2]  Adib Akl,et al.  Structure tensor based synthesis of directional textures for virtual material design , 2014, 2014 IEEE International Conference on Image Processing (ICIP).

[3]  Zhou Wang,et al.  No-reference perceptual quality assessment of JPEG compressed images , 2002, Proceedings. International Conference on Image Processing.

[4]  Adib Akl,et al.  Second-moment matrix adaptation for local orientation estimation , 2016, 2016 International Conference on Systems, Signals and Image Processing (IWSSIP).

[5]  Adib Akl,et al.  Structure tensor regularization for texture analysis , 2015, 2015 International Conference on Image Processing Theory, Tools and Applications (IPTA).

[6]  Carl-Fredrik Westin,et al.  Representing Local Structure Using Tensors II , 2011, SCIA.

[7]  Marc Donias,et al.  Structure tensor field regularization based on geometric features , 2010, 2010 18th European Signal Processing Conference.

[8]  Adib Akl,et al.  Texture Synthesis Using the Structure Tensor , 2015, IEEE Transactions on Image Processing.

[9]  Adib Akl,et al.  Two-stage Color Texture Synthesis using the Structure Tensor Field , 2015, GRAPP.

[10]  H. Knutsson.  Representing Local Structure Using Tensors , 1989 .