Results 1 - 10 of 23,343

A theory for multiresolution signal decomposition : the wavelet representation

by G. Mallat - IEEE Transaction on Pattern Analysis and Machine Intelligence , 1989
"... Abstract-Multiresolution representations are very effective for analyzing the information content of images. We study the properties of the operator which approximates a signal at a given resolution. We show that the difference of information between the approximation of a signal at the resolutions ..."
Abstract - Cited by 3538 (12 self) - Add to MetaCart
Abstract-Multiresolution representations are very effective for analyzing the information content of images. We study the properties of the operator which approximates a signal at a given resolution. We show that the difference of information between the approximation of a signal at the resolutions

SIGNAL RECOVERY BY PROXIMAL FORWARD-BACKWARD SPLITTING

by Patrick L. Combettes, Valérie R. Wajs - MULTISCALE MODEL. SIMUL. TO APPEAR
"... We show that various inverse problems in signal recovery can be formulated as the generic problem of minimizing the sum of two convex functions with certain regularity properties. This formulation makes it possible to derive existence, uniqueness, characterization, and stability results in a unifi ..."
Abstract - Cited by 509 (24 self) - Add to MetaCart
We show that various inverse problems in signal recovery can be formulated as the generic problem of minimizing the sum of two convex functions with certain regularity properties. This formulation makes it possible to derive existence, uniqueness, characterization, and stability results in a

Stable signal recovery from incomplete and inaccurate measurements,”

by Emmanuel J Candès , Justin K Romberg , Terence Tao - Comm. Pure Appl. Math., , 2006
"... Abstract Suppose we wish to recover a vector x 0 ∈ R m (e.g., a digital signal or image) from incomplete and contaminated observations y = Ax 0 + e; A is an n × m matrix with far fewer rows than columns (n m) and e is an error term. Is it possible to recover x 0 accurately based on the data y? To r ..."
Abstract - Cited by 1397 (38 self) - Add to MetaCart
Abstract Suppose we wish to recover a vector x 0 ∈ R m (e.g., a digital signal or image) from incomplete and contaminated observations y = Ax 0 + e; A is an n × m matrix with far fewer rows than columns (n m) and e is an error term. Is it possible to recover x 0 accurately based on the data y

Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images.

by Stuart Geman , Donald Geman - IEEE Trans. Pattern Anal. Mach. Intell. , 1984
"... Abstract-We make an analogy between images and statistical mechanics systems. Pixel gray levels and the presence and orientation of edges are viewed as states of atoms or molecules in a lattice-like physical system. The assignment of an energy function in the physical system determines its Gibbs di ..."
Abstract - Cited by 5126 (1 self) - Add to MetaCart
Abstract-We make an analogy between images and statistical mechanics systems. Pixel gray levels and the presence and orientation of edges are viewed as states of atoms or molecules in a lattice-like physical system. The assignment of an energy function in the physical system determines its Gibbs

Compressive sampling

by Emmanuel J. Candès , 2006
"... Conventional wisdom and common practice in acquisition and reconstruction of images from frequency data follow the basic principle of the Nyquist density sampling theory. This principle states that to reconstruct an image, the number of Fourier samples we need to acquire must match the desired res ..."
Abstract - Cited by 1441 (15 self) - Add to MetaCart
resolution of the image, i.e. the number of pixels in the image. This paper surveys an emerging theory which goes by the name of “compressive sampling” or “compressed sensing,” and which says that this conventional wisdom is inaccurate. Perhaps surprisingly, it is possible to reconstruct images or signals

Near Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?

by Emmanuel J. Candès , Terence Tao , 2004
"... Suppose we are given a vector f in RN. How many linear measurements do we need to make about f to be able to recover f to within precision ɛ in the Euclidean (ℓ2) metric? Or more exactly, suppose we are interested in a class F of such objects— discrete digital signals, images, etc; how many linear m ..."
Abstract - Cited by 1513 (20 self) - Add to MetaCart
Suppose we are given a vector f in RN. How many linear measurements do we need to make about f to be able to recover f to within precision ɛ in the Euclidean (ℓ2) metric? Or more exactly, suppose we are interested in a class F of such objects— discrete digital signals, images, etc; how many linear

Brain magnetic resonance imaging with contrast dependent on blood oxygenation.

by S Ogawa , T M Lee , A R Kay , D W Tank - Proc. Natl. Acad. Sci. USA , 1990
"... ABSTRACT Paramagnetic deoxyhemoglobin in venous blood is a naturally occurring contrast agent for magnetic resonance imaging (MRI). By accentuating the effects of this agent through the use of gradient-echo techniques in high fields, we demonstrate in vivo images of brain microvasculature with imag ..."
Abstract - Cited by 648 (1 self) - Add to MetaCart
dispersion of water proton signals is produced at the echo time. This dispersion reduces the signal intensity and the voxel appears dark in the image. These intensity losses, which at high magnetic fields (-4 T) extend significantly beyond the boundary of the blood vessel, are the source of BOLD contrast

Relations between the statistics of natural images and the response properties of cortical cells

by David J. Field - J. Opt. Soc. Am. A , 1987
"... The relative efficiency of any particular image-coding scheme should be defined only in relation to the class of images that the code is likely to encounter. To understand the representation of images by the mammalian visual system, it might therefore be useful to consider the statistics of images f ..."
Abstract - Cited by 831 (18 self) - Add to MetaCart
The relative efficiency of any particular image-coding scheme should be defined only in relation to the class of images that the code is likely to encounter. To understand the representation of images by the mammalian visual system, it might therefore be useful to consider the statistics of images

Software pipelining: An effective scheduling technique for VLIW machines

by Monica Lam , 1988
"... This paper shows that software pipelining is an effective and viable scheduling technique for VLIW processors. In software pipelining, iterations of a loop in the source program are continuously initiated at constant intervals, before the preceding iterations complete. The advantage of software pipe ..."
Abstract - Cited by 581 (3 self) - Add to MetaCart
. This compiler has been used for developing a large number of applications in the areas of image, signal and scientific processing.

A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model

by Luminita A. Vese, Tony F. Chan - INTERNATIONAL JOURNAL OF COMPUTER VISION , 2002
"... We propose a new multiphase level set framework for image segmentation using the Mumford and Shah model, for piecewise constant and piecewise smooth optimal approximations. The proposed method is also a generalization of an active contour model without edges based 2-phase segmentation, developed by ..."
Abstract - Cited by 498 (22 self) - Add to MetaCart
on The Four-Color Theorem. Finally, we validate the proposed models by numerical results for signal and image denoising and segmentation, implemented using the Osher and Sethian level set method.
Results 1 - 10 of 23,343