Results 1  10
of
1,346
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
 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 2phase segmentation, developed by ..."
Abstract

Cited by 498 (22 self)
 Add to MetaCart
the problems of vacuum and overlap; it needs only log n level set functions for n phases in the piecewise constant case; it can represent boundaries with complex topologies, including triple junctions; in the piecewise smooth case, only two level set functions formally suffice to represent any partition, based
Ideal spatial adaptation by wavelet shrinkage
 Biometrika
, 1994
"... With ideal spatial adaptation, an oracle furnishes information about how best to adapt a spatially variable estimator, whether piecewise constant, piecewise polynomial, variable knot spline, or variable bandwidth kernel, to the unknown function. Estimation with the aid of an oracle o ers dramatic ad ..."
Abstract

Cited by 1269 (5 self)
 Add to MetaCart
With ideal spatial adaptation, an oracle furnishes information about how best to adapt a spatially variable estimator, whether piecewise constant, piecewise polynomial, variable knot spline, or variable bandwidth kernel, to the unknown function. Estimation with the aid of an oracle o ers dramatic
Variational Mesh Denoising Using Total Variation and Piecewise Constant Function Space
"... Abstractâ€”Mesh surface denoising is a fundamental problem in geometry processing. The main challenge is to remove noise while preserving sharp features (such as edges and corners) and preventing generating false edges. We propose in this paper to combine total variation (TV) and piecewise constant fu ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
function space for variational mesh denoising. We first give definitions of piecewise constant function spaces and associated operators. A variational mesh denoising method will then be presented by combining TV and piecewise constant function space. It is proved that, the solution of the variational
Quantized Feedback Stabilization of Linear Systems
 IEEE Trans. Automat. Control
, 2000
"... This paper addresses feedback stabilization problems for linear timeinvariant control systems with saturating quantized measurements. We propose a new control design methodology, which relies on the possibility of changing the sensitivity of the quantizer while the system evolves. The equation that ..."
Abstract

Cited by 293 (27 self)
 Add to MetaCart
functional that maps a realvalued function into a piecewise constant function taking on a finite...
Adaptive Discontinuous Galerkin Finite Element Methods for Compressible Fluid Flows
 SIAM J. Sci. Comput
"... this paper is to discuss the a posteriori error analysis and adaptive mesh design for discontinuous Galerkin finite element approximations to systems of conservation laws. In Section 2, we introduce the model problem and formulate its discontinuous Galerkin finite element approximation. Section 3 is ..."
Abstract

Cited by 122 (17 self)
 Add to MetaCart
is a piecewise constant mesh function with h(x) = diam(n) 2 Houston e al. when x is in element n. For p Iq0, we define the following finite element space n,  {v [L()]": vl [%(n)] " Vn }, where Pp(n) denotes the set of polynomials of degree at most p over n. Given that v [Hi(n)] m
Discontinuity Meshing for Radiosity
 Third Eurographics Workshop on Rendering
, 1992
"... The radiosity method is the most popular algorithm for simulating interreflection of light between diffuse surfaces. Most existing radiosity algorithms employ simple meshes and piecewise constant approximations, thereby constraining the radiosity function to be constant across each polygonal element ..."
Abstract

Cited by 92 (2 self)
 Add to MetaCart
The radiosity method is the most popular algorithm for simulating interreflection of light between diffuse surfaces. Most existing radiosity algorithms employ simple meshes and piecewise constant approximations, thereby constraining the radiosity function to be constant across each polygonal
PiecewiseConstant Stabilization
, 1999
"... . With the help of topological necessary conditions for continuous stabilization it is shown that, in general, in order to stabilize continuous and discretetime systems one has to use timedependent or discontinuous feedback controls. On the other hand, the criterion of stabilization in the class ..."
Abstract

Cited by 5 (0 self)
 Add to MetaCart
in the class of piecewiseconstant feedbacks is established. In the context of this paper a piecewiseconstant feedback is associated with a piecewiseconstant function of the form u = u(x); where x 2 R n x : The piecewiseconstant feedback synthesis outlined here has several attractive features. First
Bayesian regression of piecewise constant functions
, 2006
"... We derive an exact and efficient Bayesian regression algorithm for piecewise constant functions of unknown segment number, boundary location, and levels. It works for any noise and segment level prior, e.g. Cauchy which can handle outliers. We derive simple but good estimates for the insegment vari ..."
Abstract

Cited by 7 (4 self)
 Add to MetaCart
We derive an exact and efficient Bayesian regression algorithm for piecewise constant functions of unknown segment number, boundary location, and levels. It works for any noise and segment level prior, e.g. Cauchy which can handle outliers. We derive simple but good estimates for the in
Threshold dynamics for the piecewise constant MumfordShah functional
 J. Comput. Phys
"... We propose an efficient algorithm for minimizing the piecewise constant MumfordShah functional of image segmentation. It is based on the threshold dynamics of Merriman, Bence, and Osher for evolving an interface by its mean curvature. We show that a very fast minimization can be achieved by alterna ..."
Abstract

Cited by 40 (1 self)
 Add to MetaCart
We propose an efficient algorithm for minimizing the piecewise constant MumfordShah functional of image segmentation. It is based on the threshold dynamics of Merriman, Bence, and Osher for evolving an interface by its mean curvature. We show that a very fast minimization can be achieved
Exact Bayesian Regression of Piecewise Constant Functions
, 2007
"... We derive an exact and efficient Bayesian regression algorithm for piecewise constant functions of unknown segment number, boundary locations, and levels. The derivation works for any noise and segment level prior, e.g. Cauchy which can handle outliers. We derive simple but good estimates for the in ..."
Abstract

Cited by 9 (3 self)
 Add to MetaCart
We derive an exact and efficient Bayesian regression algorithm for piecewise constant functions of unknown segment number, boundary locations, and levels. The derivation works for any noise and segment level prior, e.g. Cauchy which can handle outliers. We derive simple but good estimates
Results 1  10
of
1,346