image analysis
Image analysis is used as a fundamental tool for recognizing, differentiating, and quantifying diverse types of images, including grayscale and color images, multispectral images for a few discrete spectral channels or wavebands (normally less than 10), and hyperspectral images with a sequence of contiguous wavebands covering a specific spectral region (e.g., visible and near-infrared). Earlier works on image analysis were primarily confined to the computer science community, and they mainly dealt with simple images for such applications as defect detection, segmentation and classification. Nowadays, image analysis is becoming increasingly important and widespread because it can be done more conveniently, rapidly and cost effectively (Prats-Montalbán et al. 2011). Image analysis relies heavily on machine vision technology (Aguilera and Stanley 1999). The explosive growth in both hardware platforms and software frameworks has led to significant advances in the analysis of digital images.
NIH Image to ImageJ: 25 years of image analysis
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For the past 25 years NIH Image and ImageJ software have been pioneers as open tools for the analysis of scientific images. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects
Remote sensing digital image analysis
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The first edition of this book appeared 25 years ago. Since then there have been enormous advances in the availability of computing resources for the analysis of remote sensing image data, and there are many more remote sensing programs and sensors now in operation
Image analysis by Krawtchouk moments
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In this paper, a new set of orthogonal moments based on the discrete classical Krawtchouk polynomials is introduced. The Krawtchouk polynomials are scaled to ensure numerical stability, thus creating a set of weighted Krawtchouk polynomials. The set of proposed
Morphological Grayscale Reconstruction in Image Analysis : Applications and E cient Algorithms
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Morphological reconstruction is part of a set of image operators often referred to as geodesic. In the binary case, reconstruction simply extracts the connected components of a binary image I (the mask) which are\marked by a (binary) image J contained in I. This
Image analysis for the biological sciences
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Quantitative image analysis is the extraction of information from data which are in the form of pictures. The aim of this book is to cover the basics of image analysis from a statistical perspective, and with emphasis on methods relevant to the biological sciences. The book is
Document image analysis
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In the late 1980s, the prevalence of fast computers, large computer memory, and inexpensive scanners fostered an increasing interest in document image analysis . With many paper documents being sent and received via fax machines and being stored digitally
Twenty years of document image analysis in PAMI
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ABSTRACT b> Abstract /b> The contributions to document image analysis of 99 papers published in the it> IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) /it> are clustered, summarized, interpolated, interpreted, and tactfully
Bayesian image analysis : An application to single photon emission tomography
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J. INTRODUCTION Image analysis embraces a wide range of image processing tasks, including blur and noise removal, segmentation and boundary finding, and object location and identification. Traditional approaches have addressed these problems on a largely
Principal component analysis for hyperspectral image classification
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The availability of hyperspectral images expands the capability of using image classification to study detailed characteristics of objects, but at a cost of having to deal with huge data sets. This work studies the use of the principal component analysis as a preprocessing technique
Object-based image analysis : strengths, weaknesses, opportunities and threats (SWOT)
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As an emerging discipline, we propose a formal definition of OBIA, describe how OBIA came into existence, and as a road map to future research propose a fundamental objective. In order to provide potential strategies to meet this objective, we undertake a tentative SWOT ABSTRACT A novel multiresolution image analysis technique based on hierarchies of irregular tessellations generated in parallel by independent stochastic processes is presented. Like traditional image pyramids these hierarchies are constructed in a number of
Similarity-Based Unsupervised Band Selection for Hyperspectral Image Analysis .
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Band selection is a common approach to reduce the data dimensionality of hyperspectral imagery. It extracts several bands of importance in some sense by taking advantage of high spectral correlation. Driven by detection or classification accuracy, one would expect that
Introduction to hyperspectral image analysis
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Background The most significant recent breakthrough in remote sensing has been the development of hyperspectral sensors and software to analyze the resulting image data. Fifteen years ago only spectral remote sensing experts had access to hyperspectral images
Moment invariants in image analysis
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This paper aims to present a survey of object recognition/classification methods based on image moments. We review various types of moments (geometric moments, complex moments) and moment-based invariants with respect to various image degradations and
Detection of structural damage from glaucoma with confocal laser image analysis .
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Purpose. To determine which structural optic nerve head parameters measured with confocal scanning laser image analysis that best discriminate between normal persons and those with glaucoma. Methods. One randomly selected eye of 53 patients with early open
Image Analysis
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After hybridization of fluorescently labeled cDNA molecules to the microarray, the array is stimulated with a laser and the intensity of fluorescence is measured at a dense grid of pixel locations on the array. An image file is created that stores all of the pixel-level intensities Printed and handwritten music notation is intended to document musical in- formation in a legible, archival form. Both recognition and generation of music notation can of course be modeled as mappings between the printed notation and the information it represents (Figure 1) Notational
Image segmentation methods for object-based analysis and classification
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The continuously improving spatial resolution of remote sensing (RS) sensors sets new demand for applications utilising this information. The need for the more efficient extraction of information from high resolution RS imagery and the seamless integration of this AcRoss a wide variety of disciplines, the manipulation of images is an integral part of some aspect of data acquisition, analysis and reporting. Until recently, the leap from scientific image processing using a camera and calipers to digital imaging required a resident programmer and/or expensive