a new cost function based on stochastic fuzzy discrimination information measure is introduced in this paper. focusing on their significant parts, this cost function is used to find the optimal value of threshold for denoising image. it is, in fact, an extension of fuzzy entropy cost function by the present author. multivariable normal distribution is used for creating focus on significant part...

We study measures associated to Brownian motions on infinitedimensional Heisenberg-like groups. In particular, we prove that the associated path space measure and heat kernel measure satisfy a strong definition of smoothness.

In this paper, a study of environmental effects on the deformation and smoothness behavior of jointed plain concrete pavement ( JPCP) during its early age is presented. A newly constructed JPCP on US-34 near Burlington, Iowa, was instrumented and monitored during the critical time immediately following construction to identify its early-age behavior regarding temperature variations. The surface...

This paper proposes a temporally-consistent and spatially-adaptive longitudinal MR brain image segmentation algorithm, referred to as CLASSIC, which aims at obtaining accurate measurements of rates of change of regional and global brain volumes from serial MR images. The algorithm incorporates image-adaptive clustering, spatiotemporal smoothness constraints, and image warping to jointly segment...

Extensive labeled data for image annotation systems, which learn to assign class labels to image regions, is difficult to obtain. We explore a hybrid model framework for utilizing partially labeled data that integrates a generative topic model for image appearance with discriminative label prediction. We propose three alternative formulations for imposing a spatial smoothness prior on the image...

in this paper, the performance of 11 different distances for image retrieval and classification, based on color, shape and texture, is evaluated. the precision-recall measure and the correct classification rate of the k-nn classifier are used to evaluate retrieval and classification performances, respectively. the experimental results for a database of 1000 images from 10 different semantic gro...

A new approach to regularization methods for image processing is introduced and developed using as a vehicle the problem of computing dense optical ow elds in an image sequence. Standard formulations of this problem require the computationally intensive solution of an elliptic partial diierential equation which arises from the often used \smoothness constraint" type regularization. We utilize t...

Abstract. We study efficient and reliable methods of capturing and sparsely representing anisotropic structures in 3D data. As a model class for multidimensional data with anisotropic features, we introduce generalized three-dimensional cartoon-like images. This function class will have two smoothness parameters: one parameter β controlling classical smoothness and one parameter α controlling a...

Direct image formation in synthetic aperture radar (SAR) involves processing of data modeled as Fourier coefficients that lie on a polar grid. Often in such data acquisition processes, imperfections in the data cannot simply be modeled as additive or even multiplicative noise errors. In the case of SAR, errors in the data can exist due to the imprecise estimation of the round trip wave propagat...