Convergence of a block coordinate descent method for nondifferentiable minimization
Journal of Optimization Theory and Applications
Compression of facial images using the K-SVD algorithm
Journal of Visual Communication and Image Representation
Online dictionary learning for sparse coding
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Subspace pursuit for compressive sensing signal reconstruction
IEEE Transactions on Information Theory
Online Learning for Matrix Factorization and Sparse Coding
The Journal of Machine Learning Research
Recursive least squares dictionary learning algorithm
IEEE Transactions on Signal Processing
-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
IEEE Transactions on Signal Processing
Matching pursuits with time-frequency dictionaries
IEEE Transactions on Signal Processing
IEEE Transactions on Information Theory
The H.264/MPEG4 advanced video coding standard and its applications
IEEE Communications Magazine
Very low bit-rate video coding based on matching pursuits
IEEE Transactions on Circuits and Systems for Video Technology
Matching pursuit video coding .I. Dictionary approximation
IEEE Transactions on Circuits and Systems for Video Technology
Overview of the H.264/AVC video coding standard
IEEE Transactions on Circuits and Systems for Video Technology
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In this paper, we propose an online learning based intra-frame video coding approach, exploiting the texture sparsity of natural images. The proposed method is capable of learning the basic texture elements from previous frames with convergence guaranteed, leading to effective dictionaries for sparser representation of incoming frames. Benefiting from online learning, the proposed online dictionary learning based codec (ODL codec) is able to achieve a goal that the more video frames are being coded, the less non-zero coefficients are required to be transmitted. Then, these non-zero coefficients for image patches are further quantized and coded combined with dictionary synchronization. The experimental results demonstrate that the number of non-zero coefficients of each frame decreases rapidly while more frames are encoded. Compared to the off-line mode training, the proposed ODL codec, learning from video on the fly, is able to reduce the computational complexity with fast convergence. Finally, the rate distortion performance shows improvement in terms of PSNR compared with the K-SVD dictionary based compression and H.264/AVC for intra-frame video at low bit rates.