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Journal ArticleDOI

Stochastic image pyramids

TLDR
A new class of image pyramids is introduced in which a global sampling structure close to that of the twofold reduced resolution next level is generated exclusively by local processes and the probabilistic algorithm exploits local ordering relations among independent identically distributed random variables.
Abstract
A new class of image pyramids is introduced in which a global sampling structure close to that of the twofold reduced resolution next level is generated exclusively by local processes. The probabilistic algorithm exploits local ordering relations among independent identically distributed random variables. The algorithm is superior to any coin tossing based procudure and converges to an optimal sampling structure in only three steps. It can be applied to either 1- or 2-dimensional lattices. Generation of stochastic pyramids has broad applicability. We discuss in detail curve processing in 2-dimensional image pyramids and labeling the mesh in massively parallel computers. We also mention investigation of the robustness of multiresolution algorithms and a fast parallel synthesis method for nonhomogeneous anisotropic random patterns.

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Citations
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Journal ArticleDOI

Interactive image segmentation by maximal similarity based region merging

TL;DR: The proposed method automatically merges the regions that are initially segmented by mean shift segmentation, and then effectively extracts the object contour by labeling all the non-marker regions as either background or object.
Journal ArticleDOI

The adaptive pyramid: a framework for 2D image analysis

TL;DR: The concept of surviving cell as a local maximum of an interest operator as well as a root is defined as a particular surviving cell in the context of shape decomposition in the adaptive pyramid.
Journal ArticleDOI

Hierarchical image analysis using irregular tessellations

TL;DR: A novel multiresolution image analysis technique based on hierarchies of irregular tessellations generated in parallel by independent stochastic processes is presented, which adapted to the image content and artifacts of rigid resolution reduction are avoided.
Journal ArticleDOI

Building irregular pyramids by dual-graph contraction

TL;DR: The author presents a theory that allows the building of different types of hierarchies on top of such image graphs based on the properties of a pair of dual-image graphs that the reduction process should preserve, e.g. the structure of a particular input graph.
Journal ArticleDOI

A critical view of pyramid segmentation algorithms

TL;DR: It is demonstrated that the fundamental reason for this shortcoming is the subsampling introduced in the higher levels of the pyramid and the multi-resolution algorithms in general have a fundamental and inherent difficulty in analyzing elongated objects and ensuring connectivity.
References
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Book

Applied nonparametric statistics

TL;DR: In this paper, applied nonparametric statistics are applied to the problem of applied non-parametric statistical data collection in the context of the application of applied NN statistics, including:
Book

Applied nonparametric statistics

TL;DR: In this article, applied nonparametric statistics are applied to the problem of applied non-parametric statistical data collection in the context of the application of applied NN statistics, including:
Journal ArticleDOI

Computer Processing of Line-Drawing Images

TL;DR: Various forms of line drawing representation are described, different schemes of quantization are compared, and the manner in which a line drawing can be extracted from a tracing or a photographic image is reviewed.
Journal ArticleDOI

Scale-Based Description and Recognition of Planar Curves and Two-Dimensional Shapes

TL;DR: The problem of finding a description, at varying levels of detail, for planar curves and matching two such descriptions is posed and solved and the result is the ``generalized scale space'' image of a planar curve which is invariant under rotation, uniform scaling and translation of the curve.
Journal ArticleDOI

The Curvature Primal Sketch

TL;DR: An implemented algorithm is described that computes the Curvature Primal Sketch by matching the multiscale convolutions of a shape, and its performance on a set of tool shapes is illustrated.
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