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Array Set Addressing: Making the World Safe for Hexagonal Imaging

Array Set Addressing: Making the World Safe for Hexagonal Im...

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Conference on image processing - algorithms and systems viii

作者： Rummelt, Nicholas I. Wilson, Joseph N. USAF Res Lab AFRL RWGI Eglin AFB FL USA

ISBN: (纸本)9780819479259

It has been shown through various research efforts over the past few decades that there are numerous advantages to sampling images hexagonally rather than rectangularly. Despite the advantages, hexagonal imaging has not been generally accepted as being advantageous due to the lack of sensors that sample hexagonally, lack of displays for hexagonal images, and lack of an elegant addressing scheme. The advantages gained by sampling hexagonally are offset by the additional processing required to deal with the problems that are inherent with the previously proposed addressing schemes. Hence, there is insufficient motivation to develop sensors and displays that operate in the hexagonal domain. This paper introduces an addressing scheme, array set addressing, that solves the problems exhibited by other approaches. This new approach represents the hexagonal grid with a pair of rectangular arrays, supporting efficient linear algebra and image processing manipulation. Early results have shown that image processing techniques such as convolution, downsampling, calculating Euclidean distances, and vector arithmetic can be done with no more complexity than is required for processing rectangularly sampled images.

关键词： Hexagonal grid hexagonal imaging addressing image processing

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A Voting Decision Strategy for image Registration under Affine Transformation

A Voting Decision Strategy for Image Registration under Affi...

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Conference on image processing - algorithms and systems viii

作者： Almehio, Yasser Bouchafa, Samia Univ Paris 11 Inst Elect Fondamentale F-91405 Orsay France

ISBN: (纸本)9780819479259

A new motion registration method based on specific level-line grouping from two images taken at different times is proposed in this paper. Our approach is an appropriate method for matching outdoor scene image sequences taken from an on-board camera, since it is robust toward contrast changes. Moreover, it does not require any estimate of the unknown transformation between images. The image registration is performed through an efficient level-line cumulative multi-stage election procedure. Each stage provides an improvement in estimating the unknown transformation. We consider in this study that the transformation between successive images is affine, which is a valid hypothesis under small time intervals between images. Our matching process is based upon adapted primitive invariants. Particular emphasis is placed on the primitive grouping process which depends on the nature of the chosen transformation.

关键词： Motion Analysis image Registration Level-Lines Affine Transformation Geometric invariants

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image analysis and classification by spectrum enhancement: New developments

Image analysis and classification by <i>spectrum enhancement...

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Conference on image processing - algorithms and systems viii

作者： Crosta, Giovanni F. Univ Milano Bicocca Inverse Problems & Math Morphol Unit Dipartimento Sci Ambiente & Terr I-20126 Milan Italy

ISBN: (纸本)9780819479259

The "enhanced spectrum" of an image g[.] is a function h[.] of wave-number u obtained by a sequence of operations on the power spectral density of g[.]. The main properties and the available theorems on the correspondence between spectrum enhancement and spatial differentiation, of either integer or fractional order, are stated. In order to apply the enhanced spectrum to image classification, one has to go, by interpolation, from h[.] to a polynomial q[.]. The graph of q[.] provides the set of morphological descriptors of the original image, suitable for submission to a multivariate statistical classifier. Since q[.] depends on an n-tuple, Psi, of parameters which control image pre-processing, spectrum enhancement and interpolation, then one can train the classifier by tuning Psi. In fact, classifier training is more articulated and relies on a "design", whereby different training sets are processed. The best performing n-tuple, Psi*, is selected by maximizing a "design-wide" figure of merit. Next one can apply the trained classifier to recognize new images. An implementation in materials science is summarized, which includes affine regression of the 1(st) principal component against an experimental parameter.

关键词： non-linear filtering fractional differentiation quantitative morphology supervised training

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A robust and fast approach for multiple image components stitching

A robust and fast approach for multiple image components sti...

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Conference on image processing - algorithms and systems viii

作者： Jaber, Mustafa Saber, Eli Shaw, Mark Hewitt, Jim Rochester Inst Technol Chester F Carlson Ctr Imaging Sci Rochester NY 14623 USA Rochester Inst Technol Dept Microelect & Elect Engn Rochester NY 14623 USA Hewlett Packard Corp Color & Imaging Boise ID 83714 USA

ISBN: (纸本)9780819479259

In this paper, we present an algorithm for image stitching that avoids performance hindrance and memory issues in diverse image processing applications/environments. High-resolution images could be cut into smaller pieces by various applications for ease of processing, especially if they are sent over a computer network. image pieces (from several high-resolution images) could be stored as a single image-set with no information about the original images. We propose a robust stitching methodology to reconstruct the original high-resolution image(s) from a target image-set that contains components of various sizes and resolutions. The proposed algorithm consists of three major modules. The first step sorts image pieces into different planes according to their spatial position, size, and resolution. It avoids sorting overlapped pieces of the same resolution in the same plane. The second module sorts the pieces from different planes according to their content by minimizing a cost function based on Mean Absolute Difference (MAD). The third module relates neighboring pieces and determines output images. The proposed algorithm could be used at a pre-processing stage in applications such as rendering, enhancement, retrieval etc, as these cannot be carried out without access to original images as individual whole components.

关键词： image stitching image alignment image registration mosaics panorama

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A Subspace Learning Approach to Evaluating the Performance of image Fusion algorithms

A Subspace Learning Approach to Evaluating the Performance o...

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Conference on Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering viii

作者： Byrd, Kenneth A. Szu, Harold Chouikha, Mohamed U.S. Army RDECOM CERDEC NVESD (United States) Howard Univ. (United States)

ISBN: (纸本)9780819481672

The fusion of multi-spectral images is an important pre-processing operation for scientists and engineers seeking to design robust detection, recognition and identification (DRI) systems. Due to the multitude of pixel-level fusion algorithms available, there is an extreme need for reliable metrics to analyze their performance. Most recently, subspace learning methods have been applied to the field of information fusion for object recognition and classification. 1 This paper aims to extend the capabilities of existing nonlinear dimensionality reduction algorithms to a new area, evaluating the performance of image fusion algorithms. We prove that distances between points in the low dimensional embedding are essentially equivalent to the results given by estimating the amount of information transfered from source images to resultant fused images (normalized mutual information).

关键词： image Fusion Performance Metric Nonlinear Dimensionality Reduction Diffusion Map

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Efficient implementation of kurtosis based no reference image sharpness metric

Efficient implementation of kurtosis based no reference imag...

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Conference on image processing - algorithms and systems viii

作者： Ferzli, Rony Girjia, Lakshmi Ali, Walid S. Ibrahim Microsoft Corp Unified Commun Grp Redmond WA 98052 USA SirF Technol San Jose CA 95112 USA

ISBN: (纸本)9780819479259

The sharpness of an image is a function of its spectral density. Wider spectrum implies sharper image. Thus the image sharpness can be measured by measuring the shape of its spectrum. Bivariate kurtosis can be used to measure the shape and shoulder of a two dimensional probability distribution. It is known that the low frequencies correspond to the slowly changing components of an image and high frequencies correspond to faster gray level changes in the image, which gives information about the finer details such as edges. When an image is in focus, the high frequency components are maximized to define the edges sharply. Thus kurtosis, which measures the width of the shoulder of the probability distribution, corresponding to the high frequencies, can be used to measure the sharpness. This work presents efficient low complexity architecture of kurtosis based image sharpness no reference metric. The calculation of higher order moments is a computational intensive task that involves a large number of additions and multiplications. A recursive IIR filter based implementation of the moments is proposed using a cascade of single pole filters. The conducted simulation results show clearly the reduction in computation while maintaining the same accuracy.

关键词： Quality assessment sharpness embedded imaging objective metrics

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Multispectral image compression for spectral and color reproduction based on lossy to lossless coding

Multispectral image compression for spectral and color repro...

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Conference on image processing - algorithms and systems viii

作者： Shinoda, Kazuma Murakami, Yuri Yamaguchi, Masahiro Ohyama, Nagaaki Tokyo Inst Technol Interdisciplinary Grad Sch Sci & Engn Midori Ku Yokohama Kanagawa 227 Japan Tokyo Inst Technol Imaging Sci & Engn Lab Yokohama Kanagawa Japan

ISBN: (纸本)9780819479259

In this paper we propose a multispectral image compression based on lossy to lossless coding, suitable for both spectral and color reproduction. The proposed method divides a multispectral image data into two groups, RGB and residual. The RGB component is extracted from the multispectral image, for example, by using the XYZ Color Matching Functions, a color conversion matrix, and a gamma curve. The original multispectral image is estimated from RGB data encoder, and the difference between the original and the estimated multispectral images, referred as a residual component in this paper, is calculated in the encoder. Then the RGB and the residual components are encoded by JPEG2000, respectively a progressive decoding is possible from the losslessly encoded code-stream. Experimental results show that, although the proposed method is slightly inferior to JPEG2000 with a multicomponent transform in rate-distortion plot of the spectrum domain at low bit rate, a decoded RGB image shows high quality at low bit rate with primary encoding of the RGB component. Its lossless compression ratio is close to that of JPEG2000 with the integer KLT.

关键词： Multispectral image compression lossy and lossless compression JPEG2000 color reproduction sRGB

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Use of Satellite image Enhancement Procedures for Global Cloud Identification

Use of Satellite Image Enhancement Procedures for Global Clo...

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Conference on image processing - algorithms and systems viii

作者： Dim, J. R. Murakami, H. Hori, M. Earth Observat Res Ctr JAXA Tsukuba Ibaraki 3058505 Japan

ISBN: (纸本)9780819479259

As a preliminary step in the study of long-term global cloud properties variations and their contribution to the Earth radiation budget, a classification procedure to identify various types of clouds is discussed. This classification scheme highlighting the spatial heterogeneity of cloud structural arrangements is used to characterize and differentiate nine cloud types. The study takes advantage of the capacity of edge gradient operators' techniques generally used to calculate the magnitude and direction changes in the intensity function of adjacent pixels of an image, to identify the various cloud types. The specific approach, based on variations of the edge gradient magnitude and orientation, is applied on daytime global cloud physical features (cloud top temperatures derived from the 11-mu m brightness temperature imagery) obtained from the National Oceanic and Atmospheric Administration-Advanced Very-High-Resolution Radiometer (NOAA-AVHRR) satellite observations. The results obtained are compared with those of the International Satellite Cloud Climatology Project (ISCCP) cloud classification algorithm which uses cloud optical properties and pressure levels to distinguish cloud types. Results of these two procedures show good agreement but substantial differences are noticed at polar areas.

关键词： Edge gradient global cloud spatial heterogeneity cloud properties image enhancement

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Noninvasive forward-scattering system for rapid detection, characterization, and identification of bacterial colonies

Noninvasive forward-scattering system for rapid detection, c...

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Conference on Chemical and Biological Sensing viii

作者： Rajwa, Bartek Bayraktar, Bulent Banada, Padmapriya P. Huff, Karleigh Bae, Euiwon Hirleman, E. Daniel Bhunia, Arun K. Robinson, J. Paul Purdue Univ Bindley Biosci Ctr W Lafayette IN 47907 USA Purdue Univ Dept Elect & Comp Engn W Lafayette IN 47907 USA Purdue Univ Mol Food Microbiol Lab W Lafayette IN 47907 USA Purdue Univ Sch Mech Engn W Lafayette IN 47907 USA Purdue Univ Sch Vet Med Dept Basic Med Sci W Lafayette IN 47907 USA Purdue Univ Weldon Sch Biomed Engn W Lafayette IN 47907 USA

ISBN: (纸本)9780819466761

Bacterial contamination of food products puts the public at risk and also generates a substantial cost for the food-processing industry. One of the greatest challenges in the response to these incidents is rapid recognition of the bacterial agents involved. Only a few currently available technologies allow testing to be performed outside of specialized microbiological laboratories. Most current systems are based on the use of expensive PCR or antibody-based techniques, and require complicated sample preparation for reliable results. Herein, we report our efforts to develop a non-invasive optical forward-scattering system for rapid, automated identification of bacterial colonies grown on solid surfaces. The presented system employs computer-vision and pattern-recognition techniques to classify scatter patterns produced by bacterial colonies irradiated with laser light. Application of Zernike and Chebyshev moments, as well as Haralick texture descriptors for image feature extraction, allows for a very high recognition rate. An SVM algorithm was used for classification of patterns. Low error rates determined by cross-validation, reproducibility of the measurements, and robustness of the system prove that the proposed technology can be implemented in automated devices for bacterial detection.

关键词： Pathogens Laser scattering Organisms Computing systems Bacteria Detection and tracking algorithms Feature extraction image classification Contamination Solids

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Snakes on triangle meshes 1

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Workshops Bildverarbeitung fur die Medizin: Algorithmen - Systeme - Anwendungen, BVM 2005 - Workshop on image processing for Medicine: algorithms - systems - Applications, BVM 2005

作者： Bischoff, Stephan Weyand, Tobias Kobbelt, Leif Lehrstuhl für Informatik VIII RWTH Aachen 52062 Aachen Germany

ISBN: (数字)9783540264316

ISBN: (纸本)3540250522

In this work we introduce a new method for representing and evolving snakes that are constrained to lie on a prescribed surface (triangle mesh). The new representation allows to automatically adapt the snake resolution to the surface tesselation and does not need any (unstable) back-projection operations. Furthermore, it enables efficient and robust collision detection and gives us complete control on the topological behaviour of the snakes, i.e. snakes may split or merge depending on the intended task. Possible applications include enhanced mesh scissoring operations and the detection of constrictions of a surface.

关键词： Mesh generation

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