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» Applying EM Algorithm for Segmentation of Textured Images
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ICIP
2010
IEEE
13 years 6 months ago
Multiframe blind deconvolution, super-resolution, and saturation correction via incremental EM
We formulate the multiframe blind deconvolution problem in an incremental expectation maximization (EM) framework. Beyond deconvolution, we show how to use the same framework to a...
Stefan Harmeling, Suvrit Sra, Michael Hirsch, Bern...
ICIP
2009
IEEE
13 years 6 months ago
A 3D discrete curvelet based method for segmenting dynamic textures
This paper presents a new approach for segmenting a video sequence containing dynamic textures. The proposed method is based on a 2D+T curvelet transform and an octree hierarchica...
Sloven Dubois, Renaud Péteri, Michel M&eacu...
ICMCS
2005
IEEE
152views Multimedia» more  ICMCS 2005»
14 years 2 months ago
Texture-Based Remote-Sensing Image Segmentation
Typically, high-resolution remote sensing (HRRS) images contain a high level noise as well as possess different texture scales. As a result, existing image segmentation approaches...
Dihua Guo, Vijayalakshmi Atluri, Nabil R. Adam
ICIAR
2011
Springer
13 years 1 days ago
A Texture-Based Probabilistic Approach for Lung Nodule Segmentation
Producing consistent segmentations of lung nodules in CT scans is a persistent problem of image processing algorithms. Many hard-segmentation approaches are proposed in the literat...
Olga Zinoveva, Dmitry Zinovev, Stephen A. Siena, D...
ICPR
2004
IEEE
14 years 9 months ago
Texture Analysis using Level-crossing Statistics
We present a novel statistical texture descriptor employing level-crossing statistics. Images are first mapped into 1D signals using space-filling curves, such as Peano or Hilbert...
Carlos Santamaria, Miroslaw Bober, Wieslaw Szajnow...