Results 11 - 20 of 880

MULTISPECTRAL IMAGE COMPRESSION BY CLUSTER-ADAPTIVE SUBSPACE REPRESENTATION

by Hui-liang Shen, Ke Li, John H. Xin
"... Multispectral imaging has attracted much interest in color sci-ence area, for its ability in providing much more spectral in-formation than 3-channel color images. Due to the huge data volume, it is necessary to compress multispectral images for efficient transmission. This paper proposes a framewor ..."
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framework for spectral compression of multispectral image by using cluster-adaptive subspaces representation. In the framework, mul-tispectral image is initially segmented by hierarchical anal-ysis of the transform coefficients in the global subspace, and then ambiguous pixels are identified and classified

Adaptive binning of X-ray galaxy cluster images

by A. C. Fabian - Monthly Notices of the Royal Astronomical Society
"... We present a simple method for adaptively binning the pixels in an image. The algorithm groups pixels into bins of size such that the fractional error on the photon count in a bin is less than or equal to a threshold value, and the size of the bin is as small as possible. The ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
We present a simple method for adaptively binning the pixels in an image. The algorithm groups pixels into bins of size such that the fractional error on the photon count in a bin is less than or equal to a threshold value, and the size of the bin is as small as possible. The

Multi conjugate adaptive optics images of the Trapezium cluster

by H. Bouy, J. Kolb, E. Marchetti, E. L. Martín, N. Huélamo, D. Barrado Y Navascués - A&A , 2008
"... Context. High resolution version of the manuscript available of ..."
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Context. High resolution version of the manuscript available of

Adaptation of Spiking Neural Networks for Image Clustering

by Chinki Chandhok, Soni Chaturvedi , 2012
"... A Biological Neural Network or simply BNN is an artificial abstract model of different parts of the brain or nervous system, featuring essential properties of these systems using biologically realistic models. The process of segmenting images is one of the most critical ones in automatic image anal ..."
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of such networks in practical, goal-oriented applications has long been limited by the lack of appropriate unsupervised learning methods. Image clustering in realistic human sense can very well be analyzed using SNN. Spiking neural networks usually results in improved quality of segmentation reflecting the mean

AN ADAPTIVE CLUSTERING ALGORITHM BASED ON THE POSSIBILITY CLUSTERING AND ISODATA FOR MULTISPECTRAL IMAGE CLASSIFICATION

by Wenping Liu, Chih-cheng Hung, Bor-chen Kuo, Tommy Coleman
"... For a clustering algorithm, the number of clusters is a key parameter since it is directly related to the number of homogenous regions in the given image. Although ISODATA clustering algorithm can determine the number of clusters and cluster centers dynamically, it is challenging to specify so many ..."
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For a clustering algorithm, the number of clusters is a key parameter since it is directly related to the number of homogenous regions in the given image. Although ISODATA clustering algorithm can determine the number of clusters and cluster centers dynamically, it is challenging to specify so many

Multigrid adaptive image processing

by Michael Unser - In Proc. IEEE International Conference on Image Processing (ICIP , 1995
"... We consider a general weighted least squares approximation problem with a membrane spline regularization term. The key parameters in this formulation are the weighting factors which provide the possibility of a spatial adaptation. We prove that the corresponding space-varying variational problem is ..."
Abstract - Cited by 16 (2 self) - Add to MetaCart
multigrid solver can be useful for a variety of image processing tasks. In particular, we propose new multigrid solutions for noise reduction in images (adaptive smoothing spline), interpolation/reconstruction of missing image data, and image segmentation using an adaptive extension of the K

An Adaptive Logical Method for Binarization of Degraded Document Images

by Yibing Yang, Hong Yan , 2000
"... This paper describes a modified logical thresholding method for binarization of seriously degraded and very poor quality gray-scale document images. This method can deal with complex signal-dependent noise, variable background intensity caused by nonuniform illumination, shadow, smear or smudge and ..."
Abstract - Cited by 49 (1 self) - Add to MetaCart
and very low contrast. The output image has no obvious loss of useful information. Firstly, we analyse the clustering and connection characteristics of the character stroke from the run-length histogram for selected image regions and various inhomogeneous gray-scale backgrounds. Then, we propose a modified

iLamps: Geometrically aware and self-configuring projectors

by Ramesh Raskar, Jeroen van Baar, Paul Beardsley, Thomas Willwacher, Srinivas Rao, Clifton Forlines - ACM TOG , 2003
"... Projectors are currently undergoing a transformation as they evolve from static output devices to portable, environment-aware, communicating systems. An enhanced projector can determine and respond to the geometry of the display surface, and can be used in an ad-hoc cluster to create a self-configur ..."
Abstract - Cited by 137 (14 self) - Add to MetaCart
-hoc cluster of heterogeneous enhanced projectors, with a new global alignment scheme, and new parametric image transfer methods for quadric surfaces, to make a seamless projection. The work is illustrated by several prototypes and applications.

Vector Quantization of Images using Modified Adaptive Resonance Algorithm for Hierarchical Clustering

by Natalija Vlajic, Howard C., Howard C. Card - IEEE Transactions on Neural Networks
"... Most neural network (NN) algorithms used for the purpose of vector quantization (VQ) focus on the mean squared error minimization within the reference- or code- vector space. This feature frequently causes increased entropy of the information contained in the quantizer (neural network), leading to a ..."
Abstract - Cited by 5 (0 self) - Add to MetaCart
to a number of disadvantages, including more apparent distortion and more demanding transmission. A modified adaptive resonance (modified ART2) learning algorithm, which we employ in this paper, belongs to the family of NN algorithms whose main goal is the discovery of input data clusters, without

Document analysis system

by K. Y. Wong, F. M. Wahl - IBM Journal of Research and Development , 1982
"... This paper outlines the requirements and components for a proposed Document Analysis System, which assists a user in encoding printed documents for computer processing. Several critical functions have been investigated and the technical approaches are discussed. The first is the segmentation and cla ..."
Abstract - Cited by 128 (0 self) - Add to MetaCart
and classijication of digitized printed documents into regions of text and images. A nonlinear, run-length smoothing algorithm has been used for this purpose. By using the regular features of text lines, a linear adaptive classification scheme discriminates text regions from others. The second technique studied
Results 11 - 20 of 880