Download or read book Development Improvement and Assessment of Image Classification and Probability Mapping Algorithms written by Qing Wang and published by . This book was released on 2018 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remotely sensed imagery is one of the most important data sources for large-scale and multi-temporal agricultural, forestry, soil, environmental, social and economic applications. In order to accurately extract useful thematic information of the earth surface from images, various techniques and methods have been developed. The methods can be divided into parametric and non-parametric based on the requirement of data distribution, or into global and local based on the characteristics of modeling global trends and local variability, or into unsupervised and supervised based on whether training data are required, and into design-based and model-based in terms of the theory based on which the estimators are developed. The methods have their own disadvantages that impede the improvement of estimation accuracy. Thus, developing novel methods and improving the existing methods are needed. This dissertation focused on the development of a feature-space indicator simulation (FSIS), the improvement of geographically weighted sigmoidal simulation (GWSS) and k-nearest neighbors (kNN), and their assessment of land use and land cover (LULC) classification and probability (fraction) mapping of percentage vegetation cover (PVC) in Duolun County, Xilingol League, Inner Mongolia, China. The FSIS employs an indicator simulation in a high-dimensional feature space and expends derivation of indicator variograms from geographic space to feature space that leads to feature space indicator variograms (FSIV), to circumvent the issues existing in traditional indicator simulation in geostatistics. The GWSS is a stochastic and probability mapping method and considers a spatially nonstationary sample data and the local variation of an interest variable. The improved kNN, called Optimal k-nearest neighbors (OkNN), searches for an optimal number of nearest neighbors at each location based on local variability, and can be used for both classification and probability mapping. Three methods were validated and compared with several widely used approaches for LULC classification and PVC mapping in the study area. The datasets used in the study included a Landsat 8 image and a total of 920 field plots. The results obtained showed that 1) Compared with maximum likelihood classification (ML), support vector machine (SVM) and random forest (RF), the proposed FSIS classifier led to statistically significantly higher classification accuracy of six LULC types (water, agricultural land, grassland, bare soil, built-up area, and forested area); 2) Compared with linear regression (LR), polynomial regression (PR), sigmoidal regression (SR), geographically weighted regression (GWR), and geographically weighted polynomial regression (GWPR), GWSS did not only resulted in more accurate estimates of PVC, but also greatly reduced the underestimations and overestimation of PVC for the small and large values respectively; 3) Most of the red and near infrared bands relevant vegetation indices had significant contributions to improving the accuracy of mapping PVC; 4) OkNN resulted in spatially variable and optimized k values and higher prediction accuracy of PVC than the global methods; and 5) The range parameter of FSIVs was the major factor that spatially affected the classification accuracy of LULC types, but the FSIVs were less sensitive to the number of training samples. Thus, the results answered all six research questions proposed.
Download or read book Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification written by Anil Kumar and published by CRC Press. This book was released on 2020-07-19 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the state-of-art image classification methods for discrimination of earth objects from remote sensing satellite data with an emphasis on fuzzy machine learning and deep learning algorithms. Both types of algorithms are described in such details that these can be implemented directly for thematic mapping of multiple-class or specific-class landcover from multispectral optical remote sensing data. These algorithms along with multi-date, multi-sensor remote sensing are capable to monitor specific stage (for e.g., phenology of growing crop) of a particular class also included. With these capabilities fuzzy machine learning algorithms have strong applications in areas like crop insurance, forest fire mapping, stubble burning, post disaster damage mapping etc. It also provides details about the temporal indices database using proposed Class Based Sensor Independent (CBSI) approach supported by practical examples. As well, this book addresses other related algorithms based on distance, kernel based as well as spatial information through Markov Random Field (MRF)/Local convolution methods to handle mixed pixels, non-linearity and noisy pixels. Further, this book covers about techniques for quantiative assessment of soft classified fraction outputs from soft classification and supported by in-house developed tool called sub-pixel multi-spectral image classifier (SMIC). It is aimed at graduate, postgraduate, research scholars and working professionals of different branches such as Geoinformation sciences, Geography, Electrical, Electronics and Computer Sciences etc., working in the fields of earth observation and satellite image processing. Learning algorithms discussed in this book may also be useful in other related fields, for example, in medical imaging. Overall, this book aims to: exclusive focus on using large range of fuzzy classification algorithms for remote sensing images; discuss ANN, CNN, RNN, and hybrid learning classifiers application on remote sensing images; describe sub-pixel multi-spectral image classifier tool (SMIC) to support discussed fuzzy and learning algorithms; explain how to assess soft classified outputs as fraction images using fuzzy error matrix (FERM) and its advance versions with FERM tool, Entropy, Correlation Coefficient, Root Mean Square Error and Receiver Operating Characteristic (ROC) methods and; combines explanation of the algorithms with case studies and practical applications.
Download or read book Operational Remote Sensing for Sustainable Development written by M. Molenaar and published by CRC Press. This book was released on 2020-09-29 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text presents papers from the 18th EARSeL Symposium, held in Enschede, Netherlands. The papers are followed by application-oriented contributions on specific themes such as land use and nature management; water quality and pollution monitoring; and coastal zone management.
Download or read book New Approaches in Intelligent Image Analysis written by Roumen Kountchev and published by Springer. This book was released on 2016-05-19 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an Introduction and 11 independent chapters, which are devoted to various new approaches of intelligent image processing and analysis. The book also presents new methods, algorithms and applied systems for intelligent image processing, on the following basic topics: Methods for Hierarchical Image Decomposition; Intelligent Digital Signal Processing and Feature Extraction; Data Clustering and Visualization via Echo State Networks; Clustering of Natural Images in Automatic Image Annotation Systems; Control System for Remote Sensing Image Processing; Tissue Segmentation of MR Brain Images Sequence; Kidney Cysts Segmentation in CT Images; Audio Visual Attention Models in Mobile Robots Navigation; Local Adaptive Image Processing; Learning Techniques for Intelligent Access Control; Resolution Improvement in Acoustic Maps. Each chapter is self-contained with its own references. Some of the chapters are devoted to the theoretical aspects while the others are presenting the practical aspects and the analysis of the modeling of the developed algorithms in different application areas.
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 Register implementation for land cover legends written by Food and Agriculture Organization of the United Nations and published by Food & Agriculture Org.. This book was released on 2021-07-30 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: Land cover assessment and monitoring of its dynamics are essential requirements for the sustainable management of natural resources, environmental protection, food security, humanitarian programmes as well as core data for monitoring and modelling. Land Cover (LC) data are therefore fundamental in fulfilling the mandates of many United Nations (UN), international and national institutions and programmes. Despite the recognition of such importance, current users of LC data still lack access to sufficient reliable or comparable baseline LC data. These data are essential to tackle the increasing concerns in regard to food security, environmental degradation, and climate change. Critically, maintaining and restoring land resources plays a vital task in tackling climate change, securing biodiversity, and maintaining crucial ecosystem services, while ensuring resilient livelihoods and food security.
Download or read book Computer Applications written by Min Zhang and published by Springer Nature. This book was released on 2023-12-13 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set CCIS 1959 and 1960 constitutes the refereed post-conference proceedings of the 38th CCF National Conference on Computer Applications, CCF NCCA 2023, held in Suzhou, China, during July 16–20, 2023. The 39 revised full papers presented in these proceedings were carefully reviewed and selected from 197 submissions. The papers are organized in the following topical sections: Volume I: Artificial intelligence and application. Volume II: Data science and technology; pattern recognition and machine learning; network communication and security; frontier and comprehensive applications.
Download or read book Digital Image Processing and Analysis written by Scott E Umbaugh and published by CRC Press. This book was released on 2022-12-30 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital Image Enhancement, Restoration and Compression focuses on human vision-based imaging application development. Examples include making poor images look better, the development of advanced compression algorithms, special effects imaging for motion pictures and the restoration of satellite images distorted by atmospheric disturbance. This book presents a unique engineering approach to the practice of digital imaging, which starts by presenting a global model to help gain an understanding of the overall process, followed by a breakdown and explanation of each individual topic. Topics are presented as they become necessary for understanding the practical imaging model under study, which provides the reader with the motivation to learn about and use the tools and methods being explored. The book includes chapters on imaging systems and software, the human visual system, image transforms, image filtering, image enhancement, image restoration, and image compression. Numerous examples, including over 700 color images, are used to illustrate the concepts discussed. Readers can explore their own application development with any programming language, including C/C++, MATLAB®, Python and R, and software is provided for both the Windows/C/C++ and MATLAB environments. The book can be used by the academic community in teaching and research, with over 1,000 PowerPoint slides and a complete solutions manual to the over 230 included problems. It can also be used for self-study by those involved with application development, whether they are engineers, scientists or artists. The new edition has been extensively updated and includes numerous problems and programming exercises that will help the reader and student develop their skills.
Download or read book Image Analysis and Recognition written by Aurélio Campilho and published by Springer Science & Business Media. This book was released on 2008-06-16 with total page 1146 pages. Available in PDF, EPUB and Kindle. Book excerpt: Non-linear image processing -- Color photo denoising via hue, saturation and intensity diffusion / Lei He and Chenyang Xu -- Examining the role of scale in the context of the non-local-means filter / Mehran Ebrahimi and Edward R. Vrscay -- Geometrical mutliscale noise resistant method of edge detection / Agnieszka Lisowska -- A simple, general model for the affine self-similarity of images / SImon K. Alexander, Edward R. Vrscay, and Satoshi Tsurumi -- Image and video coding and encryption -- Efficient bit-rate estimation for mode decision of H. 264 / AVC / Shuwei Sun and Shuming Chen -- Introducing a two dimensional measure for watermarking capacity in images / Farzin Yaghmaee and Mansour Jamzad -- Estimating the detectability of small lesions in high resolution MR compressed images / Juan Paz, Marlen Pérez, Iroel Miranda, and Peter Schelkens -- JPEG artifact removal using error distributions of linear coefficient estimates / Mika Inki --
Download or read book Image Analysis and Recognition written by Mohamed Kamel and published by Springer. This book was released on 2013-06-05 with total page 828 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the 10th International Conference on Image Analysis and Recognition, ICIAR 2013, held in Póvoa do Varzim, Portugal, in June 2013, The 92 revised full papers presented were carefully reviewed and selected from 177 submissions. The papers are organized in topical sections on biometrics: behavioral; biometrics: physiological; classification and regression; object recognition; image processing and analysis: representations and models, compression, enhancement , feature detection and segmentation; 3D image analysis; tracking; medical imaging: image segmentation, image registration, image analysis, coronary image analysis, retinal image analysis, computer aided diagnosis, brain image analysis; cell image analysis; RGB-D camera applications; methods of moments; applications.
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 New Methods to Improve Large Scale Microscopy Image Analysis with Prior Knowledge and Uncertainty written by Stegmaier, Johannes and published by KIT Scientific Publishing. This book was released on 2017-02-08 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multidimensional imaging techniques provide powerful ways to examine various kinds of scientific questions. The routinely produced data sets in the terabyte-range, however, can hardly be analyzed manually and require an extensive use of automated image analysis. The present work introduces a new concept for the estimation and propagation of uncertainty involved in image analysis operators and new segmentation algorithms that are suitable for terabyte-scale analyses of 3D+t microscopy images.
Download or read book Intelligent Analysis of Biomedical Imaging Data for Precision Medicine written by Kuanquan Wang and published by Frontiers Media SA. This book was released on 2022-11-09 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Computational Retinal Image Analysis written by Emanuele Trucco and published by Academic Press. This book was released on 2019-11-19 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Retinal Image Analysis: Tools, Applications and Perspectives gives an overview of contemporary retinal image analysis (RIA) in the context of healthcare informatics and artificial intelligence. Specifically, it provides a history of the field, the clinical motivation for RIA, technical foundations (image acquisition modalities, instruments), computational techniques for essential operations, lesion detection (e.g. optic disc in glaucoma, microaneurysms in diabetes) and validation, as well as insights into current investigations drawing from artificial intelligence and big data. This comprehensive reference is ideal for researchers and graduate students in retinal image analysis, computational ophthalmology, artificial intelligence, biomedical engineering, health informatics, and more. Provides a unique, well-structured and integrated overview of retinal image analysis Gives insights into future areas, such as large-scale screening programs, precision medicine, and computer-assisted eye care Includes plans and aspirations of companies and professional bodies
Download or read book International Journal of Advanced Remote Sensing and GIS written by Cloud Publications and published by Cloud Publications. This book was released on 2012-01-01 with total page 3465 pages. Available in PDF, EPUB and Kindle. Book excerpt: International Journal of Advanced Remote Sensing and GIS (IJARSG, ISSN 2320 – 0243) is an open-access peer-reviewed scholarly journal publishes original research papers, reviews, case study, case reports, and methodology articles in all aspects of Remote Sensing and GIS including associated fields. This Journal commits to working for quality and transparency in its publishing by following standard Publication Ethics and Policies.
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 U S Geological Survey Professional Paper written by and published by . This book was released on 1978 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt:
