Atomic Decomposition by Basis Pursuit
SIAM Journal on Scientific Computing
Image compression using an edge adapted redundant dictionary and wavelets
Signal Processing - Sparse approximations in signal and image processing
Digital Signal Processing
Method of optimal directions for frame design
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 05
Inpainting and Zooming Using Sparse Representations
The Computer Journal
Journal of Mathematical Imaging and Vision
Image sequence denoising via sparse and redundant representations
IEEE Transactions on Image Processing
Sparse and Redundant Modeling of Image Content Using an Image-Signature-Dictionary
SIAM Journal on Imaging Sciences
Double sparsity: learning sparse dictionaries for sparse signal approximation
IEEE Transactions on Signal Processing
Sparse approximation with adaptive dictionary for image prediction
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Sparse image representations with shift-invariant tree-structured dictionaries
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Recursive least squares dictionary learning algorithm
IEEE Transactions on Signal Processing
Proximal Methods for Hierarchical Sparse Coding
The Journal of Machine Learning Research
Task-Driven Dictionary Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
IEEE Transactions on Signal Processing
Analysis of low bit rate image transform coding
IEEE Transactions on Signal Processing
Matching pursuits with time-frequency dictionaries
IEEE Transactions on Signal Processing
Sparse and shift-Invariant representations of music
IEEE Transactions on Audio, Speech, and Language Processing
Sparse geometric image representations with bandelets
IEEE Transactions on Image Processing
Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries
IEEE Transactions on Image Processing
Sparse Representation for Color Image Restoration
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
We present a dictionary learning algorithm which is tailored to the block-based image prediction problem. More precisely, we learn two related sub-dictionaries A"c and A"t, the first one (A"c) for approximating known samples in a causal neighborhood of the block to be predicted and the other one (A"t) to approximate the block to be predicted. These two dictionaries are learned so that representation vectors computed by approximating the known samples using A"c will lead to a good approximation of the block to be predicted when used together with A"t. Because of its simplicity, this method can be used for on-the-fly learning of dictionaries. The proposed method has first been evaluated for intra prediction. It has then been applied in a complete image compression algorithm. Experimental results show gains up to 3dB in terms of prediction compared to the H.264/AVC intra modes and up to 2dB in terms of rate-distortion performance.