Download or read book A Spectral textural Classifier for Digital Imagery written by Jong-hun Lee and published by . This book was released on 1990 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Image Classification Using Satellite Spectral and Textural Features written by G. Wood and published by . This book was released on 1994 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multi spectral Texture written by P. J. Whitbread and published by . This book was released on 1992 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis presents two new families of classification algorithms for pixel classification based on multi-spectral texture. The research demonstrates that algorithms making use of multispectral texture can be constructed that produce better classifications than standard algorithms at comparable computational cost.
Download or read book Land Cover Classification of Remotely Sensed Images written by S. Jenicka and published by Springer Nature. This book was released on 2021-03-10 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book introduces two domains namely Remote Sensing and Digital Image Processing. It discusses remote sensing, texture, classifiers, and procedures for performing the texture-based segmentation and land cover classification. The first chapter discusses the important terminologies in remote sensing, basics of land cover classification, types of remotely sensed images and their characteristics. The second chapter introduces the texture and a detailed literature survey citing papers related to texture analysis and image processing. The third chapter describes basic texture models for gray level images and multivariate texture models for color or remotely sensed images with relevant Matlab source codes. The fourth chapter focuses on texture-based classification and texture-based segmentation. The Matlab source codes for performing supervised texture based segmentation using basic texture models and minimum distance classifier are listed. The fifth chapter describes supervised and unsupervised classifiers. The experimental results obtained using a basic texture model (Uniform Local Binary Pattern) with the classifiers described earlier are discussed through the relevant Matlab source codes. The sixth chapter describes land cover classification procedure using multivariate (statistical and spectral) texture models and minimum distance classifier with Matlab source codes. A few performance metrics are also explained. The seventh chapter explains how texture based segmentation and land cover classification are performed using the hidden Markov model with relevant Matlab source codes. The eighth chapter gives an overview of spatial data analysis and other existing land cover classification methods. The ninth chapter addresses the research issues and challenges associated with land cover classification using textural approaches. This book is useful for undergraduates in Computer Science and Civil Engineering and postgraduates who plan to do research or project work in digital image processing. The book can serve as a guide to those who narrow down their research to processing remotely sensed images. It addresses a wide range of texture models and classifiers. The book not only guides but aids the reader in implementing the concepts through the Matlab source codes listed. In short, the book will be a valuable resource for growing academicians to gain expertise in their area of specialization and students who aim at gaining in-depth knowledge through practical implementations. The exercises given under texture based segmentation (excluding land cover classification exercises) can serve as lab exercises for the undergraduate students who learn texture based image processing.
Download or read book Evaluation of the Use of Texture for Augmenting Standard Spectral Classification Techniques of Remotely Sensed Imagery written by Ryan A. Miller and published by . This book was released on 2001 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Study of Texture Classification Using Spectral Features written by and published by . This book was released on 1982 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prior spectral feature study was not successful because of inaccuracy in 2-D spectral estimation. In this report, a generalization of Lim-Malik method is used to accurately estimate the ring and wedge spectral features for classification of textural images with a typical performance of over 80 percent correct classification for six texture classes. The results compare favorably with other texture features but require less computation using iterative algorithm. (Author).
Download or read book Optimal Selection of Textural and Spectral Features for Scene Segmentation written by Wendy Rosenblum and published by . This book was released on 1990 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: "A study is described in which optimal textural and spectral features are selected for scene segmentation. A set of 46 textural features and 3 spectral features were available for image classification. A method was developed which used a thresholded separability measure to select the best features for scene segmentation. The measure was based on the Mahalanobis distance between class means. The optimal feature selection process was applied to a variety of images and classification results using 4 features ranged from 91% to 97% with independent data sets. The use of the thresholded Mahalanobis-like distance for optimal feature selection was compared to the more common thresholded divergence separability measure and was found to choose features which were equally good for classification. The Mahalanobis-like measure had the additional advantage of using only 1/6 the time needed to calculate the divergence measure."--Abstract.
Download or read book Selection and Analysis of Optimal Textural Features for Accurate Classification of Monochrome Digitized Image Data written by Denis J. Robert and published by . This book was released on 1989 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "A feature-selection technique based on measures of global class separability in multidimensional feature space is proposed for classifying monochrome digitized imagery by machine. Feature-selection procedures are an essential step in optimal classification in reduced feature space. Textural features constitute the type of measurements used to characterize image data due to its monochrome nature. IV The ability of the proposed feature-selection technique to provide an optimal environment for classifying image pixels is measured by the Gaussian Maximum Likelihood method. The appropriateness of using textural features to characterize monochrome digital image data is assessed in similar fashion. The robustness of the proposed feature selection technique, and that of use of textural features, to provide for accurate and effective image processing is tested by analyzing several monochromatic images which contain multiple ground-cover classes, various resolutions, orientations, grey-level quantization levels, and individual textural feature parameter settings."--Abstract.
Download or read book Image Texture Analysis written by Chih-Cheng Hung and published by Springer. This book was released on 2019-06-05 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: This useful textbook/reference presents an accessible primer on the fundamentals of image texture analysis, as well as an introduction to the K-views model for extracting and classifying image textures. Divided into three parts, the book opens with a review of existing models and algorithms for image texture analysis, before delving into the details of the K-views model. The work then concludes with a discussion of popular deep learning methods for image texture analysis. Topics and features: provides self-test exercises in every chapter; describes the basics of image texture, texture features, and image texture classification and segmentation; examines a selection of widely-used methods for measuring and extracting texture features, and various algorithms for texture classification; explains the concepts of dimensionality reduction and sparse representation; discusses view-based approaches to classifying images; introduces the template for the K-views algorithm, as well as a range of variants of this algorithm; reviews several neural network models for deep machine learning, and presents a specific focus on convolutional neural networks. This introductory text on image texture analysis is ideally suitable for senior undergraduate and first-year graduate students of computer science, who will benefit from the numerous clarifying examples provided throughout the work.
Download or read book Digital Analysis of Remotely Sensed Imagery written by Jay Gao and published by McGraw Hill Professional. This book was released on 2009-05-01 with total page 689 pages. Available in PDF, EPUB and Kindle. Book excerpt: An important text that identifies and introduces new trends in image analysis Digital Analysis of Remotely Sensed Imagery provides thorough coverage of the entire process of analyzing remotely sensed data for the purpose of producing accurate representations in thematic map format. Written in easy-to-follow language with minimal technical jargon, the book explores cutting-edge techniques and trends in image analysis, as well as the relationship between image processing and other recently emerged special technologies.
Download or read book Handbook of Pattern Recognition and Computer Vision written by C. H. Chen and published by World Scientific. This book was released on 1993-08 with total page 1000 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The book provides an up-to-date and authoritative treatment of pattern recognition and computer vision, with chapters written by leaders in the field. On the basic methods in pattern recognition and computer vision, topics range from statistical pattern recognition to array grammars to projective geometry to skeletonization, and shape and texture measures."--BOOK JACKET.
Download or read book Handbook of Pattern Recognition Computer Vision written by Chi-hau Chen and published by World Scientific. This book was released on 1999 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation. Presents the latest research findings in theory, techniques, algorithms, and major applications of pattern recognition and computer vision, as well as new hardware and architecture aspects. Contains sections on basic methods in pattern recognition and computer vision, nine recognition applications, inspection and robotic applications, and architectures and technology. Some areas discussed include cluster analysis, 3D vision of dynamic objects, speech recognition, computer vision in food handling, and video content analysis and retrieval. This second edition is extensively revised to describe progress in the field since 1993. Chen is affiliated with the electrical and computer engineering department at the University of Massachusetts-Dartmouth. Annotation copyrighted by Book News, Inc., Portland, OR.
Download or read book Remote Sensing Image Analysis Including the Spatial Domain written by Steven M. de Jong and published by Springer Science & Business Media. This book was released on 2007-07-26 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remote Sensing image analysis is mostly done using only spectral information on a pixel by pixel basis. Information captured in neighbouring cells, or information about patterns surrounding the pixel of interest often provides useful supplementary information. This book presents a wide range of innovative and advanced image processing methods for including spatial information, captured by neighbouring pixels in remotely sensed images, to improve image interpretation or image classification. Presented methods include different types of variogram analysis, various methods for texture quantification, smart kernel operators, pattern recognition techniques, image segmentation methods, sub-pixel methods, wavelets and advanced spectral mixture analysis techniques. Apart from explaining the working methods in detail a wide range of applications is presented covering land cover and land use mapping, environmental applications such as heavy metal pollution, urban mapping and geological applications to detect hydrocarbon seeps. The book is meant for professionals, PhD students and graduates who use remote sensing image analysis, image interpretation and image classification in their work related to disciplines such as geography, geology, botany, ecology, forestry, cartography, soil science, engineering and urban and regional planning.
Download or read book Computers in Earth and Environmental Sciences written by Hamid Reza Pourghasemi and published by Elsevier. This book was released on 2021-09-22 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computers in Earth and Environmental Sciences: Artificial Intelligence and Advanced Technologies in Hazards and Risk Management addresses the need for a comprehensive book that focuses on multi-hazard assessments, natural and manmade hazards, and risk management using new methods and technologies that employ GIS, artificial intelligence, spatial modeling, machine learning tools and meta-heuristic techniques. The book is clearly organized into four parts that cover natural hazards, environmental hazards, advanced tools and technologies in risk management, and future challenges in computer applications to hazards and risk management. Researchers and professionals in Earth and Environmental Science who require the latest technologies and advances in hazards, remote sensing, geosciences, spatial modeling and machine learning will find this book to be an invaluable source of information on the latest tools and technologies available. Covers advanced tools and technologies in risk management of hazards in both the Earth and Environmental Sciences Details the benefits and applications of various technologies to assist researchers in choosing the most appropriate techniques for purpose Expansively covers specific future challenges in the use of computers in Earth and Environmental Science Includes case studies that detail the applications of the discussed technologies down to individual hazards
Download or read book Introductory Digital Image Processing written by John R. Jensen and published by Prentice Hall. This book was released on 1986 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Exploiting Spatial and Spectral Information in Hyperdimensional Imagery written by and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, new digital image processing methods for hyperdimensional imagery are developed and experimentally tested on remotely sensed Earth observations and medical imagery. The high dimensionality of the imagery is either inherent due to the type of measurements forming the image, as with imagery obtained with hyperspectral sensors, or the result of preprocessing and feature extraction, as with synthetic aperture radar imagery and digital mammography. In the first study, two omni-directional adaptations of gray level co-occurrence matrix analysis are developed and experimentally evaluated. The adaptations are based on a previously developed rubber band straightening transform that has been used for analysis of segmented masses in digital mammograms. The new methods are beneficial because they can be applied to imagery where the region of interest is either poorly segmented or not segmented. The methods are based on the concept of extracting circular windows around each pixel in the image which are radially resampled to derive rectangular images. The images derived from the resampling are then suitable for standard GLCM techniques. The methods were applied to both remotely sensed synthetic aperture radar imagery, for the purpose of automated detection of landslides on earthen levees, and to digital mammograms, for the purpose of automated classification of masses as either benign or malignant. Experimental results show the newly developed methods to be valuable for texture feature extraction and classification of un-segmented objects. In the second study, a new technique of using spatial information in spectral band grouping for remotely sensed hyperspectral imagery is developed and experimentally tested. The technique involves clustering the spectral bands based on similarity of spatial features extracted from each band. The newly developed technique is evaluated in automated classification systems that utilize a single classifier and systems that utilize multiple classifiers combined with decision fusion. The systems are experimentally tested on remotely sensed imagery for agricultural applications. The spatial-spectral band grouping approach is compared to uniform band windowing and spectral only band grouping. The results show that the spatial-spectral band grouping method significantly outperforms both of the comparison methods, particularly when using multiple classifiers with decision fusion.
Download or read book Handbook Of Pattern Recognition And Computer Vision 2nd Edition written by Chi Hau Chen and published by World Scientific. This book was released on 1999-03-12 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference. This indispensable handbook will continue to serve as an authoritative and comprehensive guide in the field.
