Publication
Joint Sparsity with Partially Known Support and Application to Ultrasound Imaging
Publications associées (63)
Algorithmic aspects of sparse approximations
Typical tasks in signal processing may be done in simpler ways or more efficiently if the signals to analyze are represented in a proper way. This thesis deals with some algorithmic problems related to signal approximation, more precisely, in the novel fie ...
EPFL2007Space-frequency quantization for image compression with directionlets
Martin Vetterli, Vladan Velisavljevic
The standard separable 2-D wavelet transform (WT) has recently achieved a great success in image processing because it provides a sparse representation of smooth images. However, it fails to efficiently capture 1-D discontinuities, like edges or contours. ...
2007Coarse scene geometry estimation from sparse approximations of multi-view omnidirectional images
This paper presents a framework for coarse scene geometry estimation, based on sparse representations of omnidirectional images with geometrical basis functions. We introduce a correlation model that relates sparse components in different views with local ...
2007Annihilating filter-based decoding in the compressed sensing framework - art. no. 670121
Recent results in compressed sensing or compressive sampling suggest that a relatively small set of measurements taken as the inner product with universal random measurement vectors can well represent a source that is sparse in some fixed basis. By adaptin ...
Spie-Int Soc Optical Engineering, Po Box 10, Bellingham, Wa 98227-0010 Usa2007On finding nearest neighbors in a set of compressible signals
Pierre Vandergheynst, Philippe Jost
Numerous applications demand that we manipulate large sets of very high-dimensional signals. A simple yet common example is the problem of finding those signals in a database that are closest to a query. In this paper, we tackle this problem by restricting ...
2007Image compression using an edge adapted redundant dictionary and wavelets
Pierre Vandergheynst, Lorenzo Granai, Lorenzo Peotta
Low bit rate image coding is an important problem regarding applications such as storage on low memory devices or streaming data on the internet. The state of the art in image compression is to use 2-D wavelets. The advantages of wavelet bases lie in their ...
2006Sparse image approximation with application to flexible image coding
Natural images are often modeled through piecewise-smooth regions. Region edges, which correspond to the contours of the objects, become, in this model, the main information of the signal. Contours have the property of being smooth functions along the dire ...
EPFL2005Toward sparse and geometry adapted video approximations
Video signals are sequences of natural images, where images are often modeled as piecewise-smooth signals. Hence, video can be seen as a 3D piecewise-smooth signal made of piecewise-smooth regions that move through time. Based on the piecewise-smooth model ...
EPFL2005Sparse Approximation Using M-Term Pursuits with Applications to Image and Video Compression
Pascal Frossard, Pierre Vandergheynst, Adel Rahmoune
This paper introduces an algorithm for sparse approximation in redundant dictionaries, called the M-Term Pursuit (MTP), based on the matching pursuit approach (MP). This algorithm decomposes the signal into a linear combination of selected atoms, chosen to ...
2005Image/video representation and scalable coding using redundant dictionaries
Compact or efficient representation for either images or image sequences is key operation to performing image and video processing tasks, such as compression, analysis, etc. The efficiency of an approximation is evaluated by the sparsity measure of the app ...
EPFL2005