Atom Position Coding in a Matching Pursuit Based Video Coder

After publication of our work [1], we noticed that equations (41) and (42) (in Appendix 1) were incorrect. This does not affect resulting equations. The correct equations are below:

We show that the techniques of gain-shape VQ can be used in optimizing the dictionary of the matching pursuit codec. Various performance of our method were evaluated.

OBJECTIVES The ability to analyze patterns of recorded seizure activity is important in the localization and classification of seizures. Ictal evolution is typically a dynamic process with signals composed of multiple frequencies; this can limit or complicate methods of analysis. The recently-developed matching pursuit algorithm permits continuous time-frequency analyses, making it particularly...

In this talk I will introduce marine seismic acquisition technologies and focus on solutions to maximize the bandwidth of the measured data. This involves detecting and removing the components of the wavefields that are reflected at the sea surface and that propagate downward: these downgoing reflections, called “ghosts” in literature, interfere with the upgoing wavefield, that is generated by ...

This paper studies quantization error in the context of Matching Pursuit coded streams. The quantization noise is shown to depend on error on both coefficients and indexes. It is moreover influenced by the redundancy of the Matching Pursuit dictionary. A novel general formulation of the structural redundancy in overcomplete decompositions is shown to enhance the accuracy of classical redundancy...

Extracting good representations from images is essential for many computer vision tasks. In this paper, we propose hierarchical matching pursuit (HMP), which builds a feature hierarchy layer-by-layer using an efficient matching pursuit encoder. It includes three modules: batch (tree) orthogonal matching pursuit, spatial pyramid max pooling, and contrast normalization. We investigate the archite...

On [24] some consequences of the Restricted Isometry Property (RIP) of matrices have been applied to develop a greedy algorithm called “ROMP” (Regularized Orthogonal Matching Pursuit) to recover sparse signals and to approximate non-sparse ones. These consequences were subsequently applied to other greedy and thresholding algorithms like “SThresh”, “CoSaMP”, “StOMP” and “SWCGP”. In this paper, ...

Matching pursuit was originally formulated as a technique for identifying the time/frequency content of a time series whose spectral properties evolve over time. The basic idea was to construct a large ‘dictionary’ of explanatory vectors that are localized both in time and in frequency and then to analyze a time series by projecting it against the vectors in the dictionary. Matching pursuit can...