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Fast Algorithm for Local Statistics Calculation for NDimensional Images
, 2001
"... This paper presents a fast algorithm for calculating these local statistics in a window of an Ndimensional image. The new algorithm, which is called the plunger method, recursively reduces the dimensions of the input Ndimensional image to achieve fast computation. The speed of the algorithm is ind ..."
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Cited by 2 (1 self)
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This paper presents a fast algorithm for calculating these local statistics in a window of an Ndimensional image. The new algorithm, which is called the plunger method, recursively reduces the dimensions of the input Ndimensional image to achieve fast computation. The speed of the algorithm
String Transformation for nDimensional Image Compression
 SPRINGERVERLAG BERLIN HEIDELBERG
, 2002
"... Image compression and manipulation by weighted finite automata exploit similarities in the images in order to obtain notable compression ratios and manipulation tools. The investigations are often based on twodimensional images. A natural ..."
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Cited by 2 (0 self)
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Image compression and manipulation by weighted finite automata exploit similarities in the images in order to obtain notable compression ratios and manipulation tools. The investigations are often based on twodimensional images. A natural
LPT: Eye Features Localizer in an NDimensional Image Space
"... Abstract Facial feature extraction is one of the most important challenges in the area of facial image processing. This paper introduces a new method for locating eye features that is capable of processing images rapidly while achieving high detection rates. The proposed method is applicable to an ..."
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Cited by 1 (1 self)
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to an ndimensional space. Therefore, a new representation is considered for image, where an m×n image consists of m observation sets in an ndimensional space. The main contribution to this paper is proposing a onetoone linear transform based on this new representation called Linear Principal
Scale Invariant Feature Transform for nDimensional Images (nSIFT) Release 1.00
, 2007
"... This document describes the implementation of several features previously developed[2], extending the 2D scale invariant feature transform (SIFT)[4, 5] for images of arbitrary dimensionality, such as 3D medical image volumes and time series, using ITK 1. Specifically, we provide a scale invariant im ..."
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Cited by 1 (0 self)
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This document describes the implementation of several features previously developed[2], extending the 2D scale invariant feature transform (SIFT)[4, 5] for images of arbitrary dimensionality, such as 3D medical image volumes and time series, using ITK 1. Specifically, we provide a scale invariant
Interactive Graph Cuts for Optimal Boundary & Region Segmentation of Objects in ND Images
, 2001
"... In this paper we describe a new technique for general purpose interactive segmentation of Ndimensional images. The user marks certain pixels as “object” or “background” to provide hard constraints for segmentation. Additional soft constraints incorporate both boundary and region information. Graph ..."
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Cited by 1013 (20 self)
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In this paper we describe a new technique for general purpose interactive segmentation of Ndimensional images. The user marks certain pixels as “object” or “background” to provide hard constraints for segmentation. Additional soft constraints incorporate both boundary and region information. Graph
Multimed Tools Appl
"... Linear principal transformation: toward locating features in Ndimensional image space ..."
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Linear principal transformation: toward locating features in Ndimensional image space
The Contourlet Transform: An Efficient Directional Multiresolution Image Representation
 IEEE TRANSACTIONS ON IMAGE PROCESSING
"... The limitations of commonly used separable extensions of onedimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known. In this paper, we pursue a “true” twodimensional transform that can capture the intrinsic geometrical structure t ..."
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Cited by 519 (20 self)
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The limitations of commonly used separable extensions of onedimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known. In this paper, we pursue a “true” twodimensional transform that can capture the intrinsic geometrical structure
Recognitionbycomponents: A theory of human image understanding
 Psychological Review
, 1987
"... The perceptual recognition of objects is conceptualized to be a process in which the image of the input is segmented at regions of deep concavity into an arrangement of simple geometric components, such as blocks, cylinders, wedges, and cones. The fundamental assumption of the proposed theory, recog ..."
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Cited by 1267 (23 self)
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, recognitionbycomponents (RBC), is that a modest set of generalizedcone components, called geons (N ^ 36), can be derived from contrasts of five readily detectable properties of edges in a twodimensional image: curvature, collinearity, symmetry, parallelism, and cotermmation. The detection
Near Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
, 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 ..."
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Cited by 1516 (20 self)
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as the class F of those elements whose entries obey the power decay law f  (n) ≤ C · n −1/p. We take measurements 〈f, Xk〉, k = 1,..., K, where the Xk are Ndimensional Gaussian
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